Jobs Kyiv
16-
Β· 67 views Β· 0 applications Β· 3d
Data Scientist
Ukraine Β· Product Β· 1 year of experience Β· Pre-IntermediateΠ ΠΊΠΎΠΌΠ°Π½Π΄Ρ 10 Π΄Π°ΡΠ° ΡΠ°ΡΠ½ΡΠΈΡΡΡΠ². ΠΡΠ°ΡΡΡΡΡ Π· ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΡΠΈΠ½Π³Ρ, ΠΎΡΡΠ½ΠΊΠΈ ΡΠΈΠ·ΠΈΠΊΡ Π»ΡΠΊΠ²ΡΠ΄Π½ΠΎΡΡΡ, ΠΊΠΎΠ»Π΅ΠΊΡΠ½Ρ, Π°Π½ΡΠΈΡΡΠΎΠ΄Ρ, ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ. ΠΡΠ½ΠΎΠ²Π½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ ΠΠΠΠ'Π―ΠΠΠΠΠ 1+ ΡΡΠΊ ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΡΠ²ΡΠ΄Ρ Π½Π° Π°Π½Π°Π»ΠΎΠ³ΡΡΠ½ΡΠΉ ΠΏΠΎΡΠ°Π΄Ρ ΠΠ°ΠΊΡΠ½ΡΠ΅Π½Π° Π²ΠΈΡΠ° ΠΎΡΠ²ΡΡΠ° (ΡΡΠ·ΠΈΠΊΠΎ-ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½Π°,...Π ΠΊΠΎΠΌΠ°Π½Π΄Ρ 10 Π΄Π°ΡΠ° ΡΠ°ΡΠ½ΡΠΈΡΡΡΠ². ΠΡΠ°ΡΡΡΡΡ Π· ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΡΠΈΠ½Π³Ρ, ΠΎΡΡΠ½ΠΊΠΈ ΡΠΈΠ·ΠΈΠΊΡ Π»ΡΠΊΠ²ΡΠ΄Π½ΠΎΡΡΡ, ΠΊΠΎΠ»Π΅ΠΊΡΠ½Ρ, Π°Π½ΡΠΈΡΡΠΎΠ΄Ρ, ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ.
ΠΡΠ½ΠΎΠ²Π½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ
- ΠΠΠΠ'Π―ΠΠΠΠΠ 1+ ΡΡΠΊ ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΡΠ²ΡΠ΄Ρ Π½Π° Π°Π½Π°Π»ΠΎΠ³ΡΡΠ½ΡΠΉ ΠΏΠΎΡΠ°Π΄Ρ
- ΠΠ°ΠΊΡΠ½ΡΠ΅Π½Π° Π²ΠΈΡΠ° ΠΎΡΠ²ΡΡΠ° (ΡΡΠ·ΠΈΠΊΠΎ-ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½Π°, ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ°, ΠΊΠΎΠΌΠΏ'ΡΡΠ΅ΡΠ½Ρ Π½Π°ΡΠΊΠΈ)
- Π‘ΠΊΡΡΠΏΡΠ»ΡΠΎΠ·Π½ΡΡΡΡ, ΡΠ²Π°ΠΆΠ½ΡΡΡΡ Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Π»ΡΠ½ΡΡΡΡ
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ, Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΡΠ° ΡΡΠΏΡΠΎΠ²ΠΎΠ΄ΠΆΠ΅Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
- ΠΠΎΡΠ²ΡΠ΄ Π½Π°ΠΏΠΈΡΠ°Π½Π½Ρ ΠΊΠ»Π°ΡΡΠ², ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½ΡΠ²
- ΠΠ½Π°Π½Π½Ρ Python
- ΠΠ°ΡΠ½Π΅ Π·Π½Π°Π½Π½Ρ SQL (Π°Π½Π°Π»ΡΠ·ΡΡΠΌΠΎ Π½Π°ΠΉΠ±ΡΠ»ΡΡΡ Π· ΡΡΡΡ Π±Π°Π½ΠΊΡΠ² Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ )
- ΠΠ½Π°Π½Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΠΈΡ Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ² ML (ΠΊΠ»Π°ΡΠΈΡΠ½ΠΈΠΉ ML, ΡΠ΅Π³ΡΠ΅ΡΡΡ, ΠΊΠ»Π°ΡΠΈΡΡΠΊΠ°ΡΡΡ, ΠΏΡΠΎΠ³Π½ΠΎΠ· ΡΠ°ΡΠΎΠ²ΠΈΡ ΡΡΠ΄ΡΠ²)
ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Ρ ΡΡΠ½ΡΠ΅Ρ Π΄ΠΎΠΌΠ΅Π½Ρ
- ΠΠΎΡΠ²ΡΠ΄ Π· Amazon Sagemaker, Amazon S3
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Git
ΠΡΠ½ΠΎΠ²Π½Ρ ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΈ
- ΠΠ½Π°Π»ΡΠ· ΡΠ° Π²Π°Π»ΡΠ΄Π°ΡΡΡ Π΄Π°Π½ΠΈΡ
- Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΡΠ° Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΎΡΡΠ½ΠΊΠΈ ΡΠΈΠ·ΠΈΠΊΡΠ², ΡΠΊΡ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°ΡΡΡ ΠΊΡΠ°ΡΠΈΠΌ ΡΠ²ΡΡΠΎΠ²ΠΈΠΌ ΠΏΡΠ°ΠΊΡΠΈΠΊΠ°ΠΌ
- ΠΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎΡ ΡΠΊΠΎΡΡΡ
Π‘Π²ΠΎΡΠΌ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΠ°ΠΌ ΠΌΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ
- Π ΠΎΠ±ΠΎΡΡ Π² Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΎΠΌΡ ΡΠ° ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΎΠΌΡ Π±Π°Π½ΠΊΡ Π£ΠΊΡΠ°ΡΠ½ΠΈ
- ΠΡΡΡΡΠΉΠ½Π΅ ΠΏΡΠ°ΡΠ΅Π²Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΡΠ° 24 ΠΊΠ°Π»Π΅Π½Π΄Π°ΡΠ½ΠΈΡ Π΄Π½Ρ Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ
- ΠΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ Π»ΡΠΊΠ°ΡΠ½ΡΠ½ΠΈΡ
- ΠΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½Ρ Π·Π°ΡΠΎΠ±ΡΡΠ½Ρ ΠΏΠ»Π°ΡΡ
- ΠΠΎΠ½ΡΡΠΈ, ΠΏΡΠ΅ΠΌΡΡ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ Π΄ΠΎ ΠΏΠΎΠ»ΡΡΠΈΠΊΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ
- ΠΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π΅ Π½Π°Π²ΡΠ°Π½Π½Ρ
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π²ΡΠ΄Π΄Π°Π»Π΅Π½ΠΎΠ³ΠΎ ΡΠΎΡΠΌΠ°ΡΡ ΡΠΎΠ±ΠΎΡΠΈ
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Ρ ΡΡΠ½Π°Π½ΡΠΎΠ²Ρ Π΄ΠΎΠΏΠΎΠΌΠΎΠ³Ρ Ρ ΠΊΡΠΈΡΠΈΡΠ½ΠΈΡ ΡΠΈΡΡΠ°ΡΡΡΡ
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Β· 49 views Β· 1 application Β· 4d
Senior / Lead AI and ML Data Scientist to $7000
Ukraine Β· Product Β· 5 years of experience Β· IntermediateΠΠΎΠΌΠ°Π½Π΄Π°, ΡΠΎ Ρ Π²Π΅Π»ΠΈΠΊΠΈΠΌ fashion-retail Π³ΡΠ°Π²ΡΠ΅ΠΌ ΡΠ²ΡΡΠΎΠ²ΠΎΠ³ΠΎ ΡΠΈΠ½ΠΊΡ Π·Π°ΠΏΡΠΎΡΡΡ Π΄ΠΎ ΡΠ΅Π±Π΅ Senior / Lead AI and ML Data Scientist! ΠΡΠ½ΠΎΠ²Π½Ρ ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΈ Π½Π° ΠΏΠΎΡΠ°Π΄Ρ: β’ ΠΡΠΎΠ΅ΠΊΡΡΠ²Π°Π½Π½Ρ Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ Π°ΡΡ ΡΡΠ΅ΠΊΡΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠΈ; β’ ΠΠ±ΡΠΎΠ±ΠΊΠ°, ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° Ρ Π°Π½Π°Π»ΡΠ· Π΄Π°Π½ΠΈΡ ; β’ Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° Ρ...ΠΠΎΠΌΠ°Π½Π΄Π°, ΡΠΎ Ρ Π²Π΅Π»ΠΈΠΊΠΈΠΌ fashion-retail Π³ΡΠ°Π²ΡΠ΅ΠΌ ΡΠ²ΡΡΠΎΠ²ΠΎΠ³ΠΎ ΡΠΈΠ½ΠΊΡ Π·Π°ΠΏΡΠΎΡΡΡ Π΄ΠΎ ΡΠ΅Π±Π΅ Senior / Lead AI and ML Data Scientist!
ΠΡΠ½ΠΎΠ²Π½Ρ ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΈ Π½Π° ΠΏΠΎΡΠ°Π΄Ρ:
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β’ ΠΡΠΎΠ΅ΠΊΡΡΠ²Π°Π½Π½Ρ Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ Π°ΡΡ ΡΡΠ΅ΠΊΡΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠΈ;
β’ ΠΠ±ΡΠΎΠ±ΠΊΠ°, ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° Ρ Π°Π½Π°Π»ΡΠ· Π΄Π°Π½ΠΈΡ ;
β’ Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° Ρ ΡΠ΅ΡΡΡΠ²Π°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ, Π° ΡΠ°ΠΊΠΎΠΆ ΡΡ Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ;
β’ Π‘ΡΠΏΡΠΎΠ²ΡΠ΄ ΡΡΠ½ΡΡΡΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
β’ ΠΠ°ΡΡΠΎΡΡΠ²Π°Π½Π½Ρ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ½ΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΡΠ² Π΄Π»Ρ Π°Π½Π°Π»ΡΠ·Ρ Ρ ΡΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΡΡ Π΄Π°Π½ΠΈΡ , ΠΏΠΎΡΡΠΊ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΡΡΠ½ΠΎΡΡΠ΅ΠΉ ΡΠ° ΡΠ½ΡΠ°ΠΉΡΡΠ² Π΄Π»Ρ ΠΏΠΎΠ»ΡΠΏΡΠ΅Π½Π½Ρ ΡΠΊΠΎΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
β’ ΠΠ²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΡΡ Ρ ΡΠ°Π±Π»ΠΎΠ½ΡΠ·Π°ΡΡΡ Π·Π°Π²Π΄Π°Π½Ρ, ΡΠΎ ΠΏΠΎΠ²ΡΠΎΡΡΡΡΡΡΡ;
β’ Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° Ρ ΡΡΠΏΡΠΎΠ²ΡΠ΄ Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ² Π΄Π»Ρ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°ΡΡΠΉΠ½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ;
β’ Π‘ΠΏΡΠ²ΠΏΡΠ°ΡΡ Π· ΠΊΡΠΎΡΡ-ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΌΠΈ ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌΠΈ Π΄Π»Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ ΡΡΡΠ΅Π½Ρ;
β’ ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΡΠ·Ρ Π½Π° Π²Π΅Π»ΠΈΠΊΠΈΡ ΠΌΠ°ΡΠΈΠ²Π°Ρ Π΄Π°Π½ΠΈΡ Π΄Π»Ρ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½Π½Ρ ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΈΠΉΠ½ΡΡΡΡ Π±ΡΠ·Π½Π΅Ρ-ΡΡΡΠ΅Π½Ρ.
ΠΠ°ΡΡ ΠΏΠΎΠ±Π°ΠΆΠ°Π½Π½Ρ Π΄ΠΎ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΠ°:
β’ 3+ ΡΠΎΠΊΠΈ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΡΠ²ΡΠ΄Ρ;
β’ 5+ ΡΠΎΠΊΡΠ² Python, R Ρ ΠΏΠΎΠ²'ΡΠ·Π°Π½ΠΈΡ Π· Π½ΠΈΠΌ ΠΏΠ°ΠΊΠ΅ΡΡΠ², ΡΠ°ΠΊΠΈΡ ΡΠΊ Scikit - learn, Shap, Pandas;
β’ ΠΠΈΡΠΎΠΊΠΈΠΉ ΡΡΠ²Π΅Π½Ρ Π·Π½Π°Π½Ρ Π² SQL (CTE, window functions);
β’ ΠΠΏΠ΅Π²Π½Π΅Π½Π½Ρ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½Ρ Π·Π½Π°Π½Π½Ρ ( ΠΏΠ΅ΡΠ΅Π²Π°ΠΆΠ½ΠΎ ΠΎΡΠ²ΡΡΠ° Π² ΠΎΠ±Π»Π°ΡΡΡ ΠΊΠΎΠΌΠΏ'ΡΡΠ΅ΡΠ½ΠΈΡ Π½Π°ΡΠΊ Π°Π±ΠΎ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ);
β’ ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Π²Π΅Π»ΠΈΠΊΠΈΠΌΠΈ ΠΌΠ°ΡΠΈΠ²Π°ΠΌΠΈ Π΄Π°Π½ΠΈΡ , ΡΡΠ°ΡΠΈΡΡΠΈΡΠ½ΠΈΠΌ Π°Π½Π°Π»ΡΠ·ΠΎΠΌ, Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°ΠΌΠΈ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΎΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
β’ ΠΡΠ΄ΠΌΡΠ½Π½Ρ ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΠΈΠ²Π½Ρ Π½Π°Π²ΠΈΡΠΊΠΈ Π΄Π»Ρ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡ Π²Π·Π°ΡΠΌΠΎΠ΄ΡΡ ΡΠ· Π·Π°ΡΡΠΊΠ°Π²Π»Π΅Π½ΠΈΠΌΠΈ ΡΡΠΎΡΠΎΠ½Π°ΠΌΠΈ ( ΡΠΊ ΡΠ΅Ρ Π½ΡΡΠ½ΠΎΠ³ΠΎ ΡΠ°ΠΊ Ρ Π½Π΅ ΡΠ΅Ρ Π½ΡΡΠ½ΠΎΠ³ΠΎ Ρ Π°ΡΠ°ΠΊΡΠ΅ΡΡ).
ΠΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ Π±ΡΠ΄Π΅:
β’ ΠΠ΄Π°ΡΠ½ΡΡΡΡ Π²ΠΈΡΠ²Π»ΡΡΠΈ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½Ρ ΡΡΠ΅Π½Π°ΡΡΡ Π΄Π»Ρ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ Π΄ΠΎΠ΄Π°ΡΠΊΠΎΠ²ΠΈΡ ΡΡΠ½Π½ΠΎΡΡΠ΅ΠΉ Ρ Π±ΡΠ·Π½Π΅ΡΡ;
β’ ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Ρ ΡΡΠ΅ΡΡ ΡΠΎΠ·Π΄ΡΡΠ±Π½ΠΎΡ ΡΠΎΡΠ³ΡΠ²Π»Ρ;
β’ ΠΠ½Π°ΠΉΠΎΠΌΡΡΠ²ΠΎ Π· ΡΡΠ΅ΠΉΠΌΠ²ΠΎΡΠΊΠ°ΠΌΠΈ Ρ Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠ°ΠΌΠΈ ΡΡΡΡΠ½ΠΎΠ³ΠΎ ΡΠ½ΡΠ΅Π»Π΅ΠΊΡΡ, ΡΠ°ΠΊΠΈΠΌΠΈ ΡΠΊ TensorFlow, PyTorch Π°Π±ΠΎ Langchain;
β’ ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΡΡΠΌ Scientific Python (NumPy, pandas, Scikit - learn, Keras / TensorFlow Π°Π±ΠΎ PyTorch);
β’ ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡΠΌΠΈ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ Π²Π΅Π»ΠΈΠΊΠΈΡ Π΄Π°Π½ΠΈΡ , ΡΠ°ΠΊΠΈΠΌΠΈ ΡΠΊ Hadoop, Spark Π°Π±ΠΎ Hive;
β’ ΠΠΎΡΠ²ΡΠ΄ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ½ΠΈΡ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Ρ Ρ A/B- ΡΠ΅ΡΡΡΠ²Π°Π½Π½Ρ;
β’ ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ Ρ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ Π²ΡΠ·ΡΠ°Π»ΡΠ·Π°ΡΡΡ Π΄Π°Π½ΠΈΡ . -
Β· 32 views Β· 1 application Β· 9d
Game Mathematician
Office Work Β· Ukraine (Kyiv) Β· Product Β· 2 years of experienceWelcome to King Group - a place where the best people from the IT and gambling industries meet to do amazing things together. We operate numerous projects in the iGaming sector in the markets of Ukraine, Europe and the USA, invest in venture startups,...Welcome to King Group - a place where the best people from the IT and gambling industries meet to do amazing things together. We operate numerous projects in the iGaming sector in the markets of Ukraine, Europe and the USA, invest in venture startups, promising ideas and people.
One of our companies is a game studio that deals with the full cycle of iGaming product development. From idea to release, we combine creativity, modern technologies and deep analytics to create a unique gaming experience. Our mission is to excite, inspire and shape the future of the industry.
Our company is looking for a math expert who has a drive and passion (perhaps some experience) for games.
Key skills (it's not necessary to have all key skills, but more is better than less):
- Higher education in mathematics or related fields (related to research, analytics or data processing);
- Have a strong math background (especially probability theory, statistics, combinatorics);
- Advanced knowledge of MS Excel (statistical, mathematical functions);
- Be proficient at one (at least) programming language (Python is preferable);
- Knowledge of one of the CAS (Mathematica, Mathcad, Maxima);
- Have a strong math background (especially probability theory, statistics, combinatorics);
- Have previous experience in gaming industry or (and) have experience in playing slots (or any other probabilistic games (poker, blackjack, etc));
- Understand the time and memory complexity of your code;
- Be keen on details (Yes, it's really important at this position);
- Understanding OOP Concepts;
- Experience in developing mathematical models.
Nice to have:
- Experience in using git;
- Experience in using JIRA.
Responsibilities:
- Prepare math for slot games;
- Discuss with business/ propose new game ideas/new feature ides;
- Implement game logic of new features, games;
- Gather games' statistics by precise calculations / running simulations of the games;
- Make games attractive for players from the math side.
Why NetGame:
- Social Package;
- Medical care;
- Sick Days;
- Professional development support;
- Family-like atmosphere. You can check it out yourself ;)
- Great career prospects.
Do you want to grow with us? Do you have the desire to take an active part in creating a product? Send your resume and let's get to know each other ;)
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Β· 20 views Β· 0 applications Β· 10d
Senior Data Scientist
Ukraine Β· Product Β· 5 years of experience Ukrainian Product πΊπ¦Π ΠΊΠΎΠΌΠ°Π½Π΄Ρ DataDiscovery ΡΡΠΊΠ°ΡΠΌΠΎ Π½Π° ΡΠΎΠ·ΡΠΈΡΠ΅Π½Π½Ρ Senior Data Scientist. ΠΠ°Ρ ΡΠ΄Π΅Π°Π»ΡΠ½ΠΈΠΉ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ ΠΌΠ°Ρ: - 5+ ΡΠΎΠΊΠΈ ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΡΠ²ΡΠ΄Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ. ΠΠ°Π²ΠΈΡΠΊΠΈ: - Python ΡΠ° Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠΈ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ: TensorFlow, PyTorch; - Π’Π΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡ Big Data: Kafka, Amazon...Π ΠΊΠΎΠΌΠ°Π½Π΄Ρ DataDiscovery ΡΡΠΊΠ°ΡΠΌΠΎ Π½Π° ΡΠΎΠ·ΡΠΈΡΠ΅Π½Π½Ρ Senior Data Scientist.
ΠΠ°Ρ ΡΠ΄Π΅Π°Π»ΡΠ½ΠΈΠΉ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ ΠΌΠ°Ρ:
- 5+ ΡΠΎΠΊΠΈ ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΡΠ²ΡΠ΄Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ.
ΠΠ°Π²ΠΈΡΠΊΠΈ:
- Python ΡΠ° Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠΈ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ: TensorFlow, PyTorch;
- Π’Π΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡ Big Data: Kafka, Amazon S3, Spark;
- SQL ΡΠ° Π°Π½Π°Π»ΡΠ· Π΄Π°Π½ΠΈΡ : ΡΠΎΠ±ΠΎΡΠ° Π· Π±ΡΠ΄Ρ-ΡΠΊΠΈΠΌΠΈ Π΄ΠΆΠ΅ΡΠ΅Π»Π°ΠΌΠΈ Π΄Π°Π½ΠΈΡ (SQL, noSQL, Π²Π΅ΠΊΡΠΎΡΠ½Ρ Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ , column-oriented Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ , ΡΠΎΡΠΎ);
- Π₯ΠΌΠ°ΡΠ½Ρ ΠΏΠ»Π°ΡΡΠΎΡΠΌΠΈ: AWS, GCP;
ΠΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½Π° ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ°: ΡΠ΅Π³ΡΠ΅ΡΡΡ, ΡΠΎΠ·ΠΏΠΎΠ΄ΡΠ» ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎΡΡΠ΅ΠΉ, - ΠΏΠ΅ΡΠ΅Π²ΡΡΠΊΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ½ΠΈΡ Π³ΡΠΏΠΎΡΠ΅Π· ΡΠΎΡΠΎ;
- ΠΡΠ΄Ρ ΠΎΠ΄ΠΈ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ: ΡΠ΅Π³ΡΠ΅ΡΡΡ, ΠΊΠ»Π°ΡΡΠ΅ΡΠΈΠ·Π°ΡΡΡ, Π΄Π΅ΡΠ΅Π²Π° ΡΡΡΠ΅Π½Ρ ΡΠ° ΡΠ½ΡΡ;
- ΠΠ»Π³ΠΎΡΠΈΡΠΌΠΈ Π³Π»ΠΈΠ±ΠΎΠΊΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ: transformers, reinforcement learning, autoencoders, diffusion models, ΡΠΎΡΠΎ;
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΡΠ² AI: NLP, CV, Recsys, Generative AI;
- MLOps.
Π©ΠΎ ΠΏΠΎΡΡΡΠ±Π½ΠΎ ΡΠΎΠ±ΠΈΡΠΈ:
- ΠΠΈΡΡΡΡΠ²Π°ΡΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ²Ρ ΡΠ° Π΄ΠΎΡΠ»ΡΠ΄Π½ΠΈΡΡΠΊΡ Π²ΠΈΠΊΠ»ΠΈΠΊΠΈ ΠΊΡΡΡΠΎΠ³ΠΎ ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΠ΄ΡΠΊΡΡ;
- ΠΡΠ°ΡΡΠ²Π°ΡΠΈ Π· ΡΠ΅Π°Π»ΡΠ½ΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ ΡΠ΅Π°Π»ΡΠ½ΠΈΡ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠ²;
- ΠΠΈΠ²ΡΠ°ΡΠΈ ΡΠ° Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΡΠ²Π°ΡΠΈ ΡΠΊΠ»Π°Π΄Π½Ρ state-of-the-art Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈ Π² ΠΎΠ±Π»Π°ΡΡΡ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Π΄Π»Ρ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ ΠΏΡΠ°ΠΊΡΠΈΡΠ½ΠΈΡ Π·Π°Π΄Π°Ρ;
- ΠΡΡΠ½ΡΠ²Π°ΡΠΈ ΡΠ΅Ρ Π½ΡΡΠ½Ρ ΠΊΠΎΠΌΠΏΡΠΎΠΌΡΡΠΈ ΠΏΠΎ ΠΊΠΎΠΆΠ½ΠΎΠΌΡ ΡΡΡΠ΅Π½Π½Ρ;
- ΠΡΠ°ΡΡΠ²Π°ΡΠΈ Π² ΡΡΡΠ½ΠΎΠΌΡ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΡΡΠ²Ρ Π· ΡΠ½ΡΠΈΠΌΠΈ ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌΠΈ Π΄Π»Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π½ΠΎΠ²ΠΈΡ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΠ΅ΠΉ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡΠ² AI.
Π©ΠΎ ΠΌΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- Π ΠΎΠ±ΠΎΡΡ Π² ΡΡΠ°Π±ΡΠ»ΡΠ½ΡΠΉ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ β Π°Π΄ΠΆΠ΅ ΠΌΠΈ ΠΏΠΎΠ½Π°Π΄ 10 ΡΠΎΠΊΡΠ² Π½Π° ΡΠΈΠ½ΠΊΡ;
- ΠΡΠΉΡΠ½ΠΎ ΡΡΠΊΠ°Π²Ρ Π·Π°Π²Π΄Π°Π½Π½Ρ: Π±Π΅ΡΠΈ ΡΡΠ°ΡΡΡ Ρ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΠΌΠ΅Π΄ΡΠ°ΡΠ΅ΡΠ²ΡΡΡ ΠΌΠ°ΠΉΠ±ΡΡΠ½ΡΠΎΠ³ΠΎ;
- ΠΡΠ΄Π½ΠΎΡΠΈΠ½ΠΈ, ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²Π°Π½Ρ Π½Π° Π΄ΠΎΠ²ΡΡΡ;
- ΠΠ°Π³Π°ΡΠΎ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΠ΅ΠΉ Π΄Π»Ρ ΡΠΎΠ·Π²ΠΈΡΠΊΡ;
- ΠΠ΅ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎ ΠΊΡΡΡΡ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²ΠΈ;
- ΠΠ΅Π·ΠΊΠΎΡΡΠΎΠ²Π½Ρ ΡΡΠΎΠΊΠΈ Π°Π½Π³Π»ΡΠΉΡΡΠΊΠΎΡ ΠΌΠΎΠ²ΠΈ;
- ΠΠ°Π½ΡΡΡΡ Π· ΠΏΠ»Π°Π²Π°Π½Π½Ρ, Π° ΡΠ°ΠΊΠΎΠΆ ΡΡΠΎΠΊΠΈ Π½Π°ΡΡΠΎΠ»ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅Π½ΡΡΡ;
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΏΡΠΈΡ ΠΎΠ»ΠΎΠ³Π°;
- ΠΠ»Ρ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΡΠ² ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π·Π½ΠΈΠΆΠΊΠΈ Π²ΡΠ΄ Π±ΡΠ΅Π½Π΄ΡΠ² ΠΏΠ°ΡΡΠ½Π΅ΡΡΠ².
ΠΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°ΡΡΠΈ Π½Π° Π²Π°ΠΊΠ°Π½ΡΡΡ Ρ Π½Π°Π΄ΡΡΠ»Π°Π²ΡΠΈ ΡΠ²ΠΎΡ ΡΠ΅Π·ΡΠΌΠ΅ Π² ΠΠΎΠΌΠΏΠ°Π½ΡΡ (Π’ΠΠ Β«ΠΠΠΠΠΠΒ»), Π·Π°ΡΠ΅ΡΡΡΡΠΎΠ²Π°Π½Ρ ΠΉ Π΄ΡΡΡΡ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ Π΄ΠΎ Π·Π°ΠΊΠΎΠ½ΠΎΠ΄Π°Π²ΡΡΠ²Π° Π£ΠΊΡΠ°ΡΠ½ΠΈ, ΡΠ΅ΡΡΡΡΠ°ΡΡΠΉΠ½ΠΈΠΉ Π½ΠΎΠΌΠ΅Ρ 38347009, Π°Π΄ΡΠ΅ΡΠ°: Π£ΠΊΡΠ°ΡΠ½Π°, 01011, ΠΌΡΡΡΠΎ ΠΠΈΡΠ², Π²ΡΠ».Π ΠΈΠ±Π°Π»ΡΡΡΠΊΠ°, Π±ΡΠ΄ΠΈΠ½ΠΎΠΊ 22 (Π΄Π°Π»Ρ Β«ΠΠΎΠΌΠΏΠ°Π½ΡΡΒ»), Π²ΠΈ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΡΡΡΠ΅ ΡΠ° ΠΏΠΎΠ³ΠΎΠ΄ΠΆΡΡΡΠ΅ΡΡ Π· ΡΠΈΠΌ, ΡΠΎ ΠΠΎΠΌΠΏΠ°Π½ΡΡ ΠΎΠ±ΡΠΎΠ±Π»ΡΡ Π²Π°ΡΡ ΠΎΡΠΎΠ±ΠΈΡΡΡ Π΄Π°Π½Ρ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ Ρ Π²Π°ΡΠΎΠΌΡ ΡΠ΅Π·ΡΠΌΠ΅, Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ Π΄ΠΎ ΠΠ°ΠΊΠΎΠ½Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ Β«ΠΡΠΎ Π·Π°Ρ ΠΈΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Β» ΡΠ° ΠΏΡΠ°Π²ΠΈΠ» GDPR.
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Β· 27 views Β· 6 applications Β· 10d
Data Scientist/ML Engineer
Ukraine Β· 4 years of experience Β· Upper-IntermediateΠΡΡΠ°Ρ! Π¨ΡΠΊΠ°ΡΠΌΠΎ Π΄ΠΎΡΠ²ΡΠ΄ΡΠ΅Π½ΠΎΠ³ΠΎ Data Scientist/ML Engineer Π΄Π»Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΡΡΡΠ΅Π½Ρ Π΄Π»Ρ Π²ΡΡΡΡΠ°Π»ΡΠ½ΠΎΡ Π΅Π»Π΅ΠΊΡΡΠΎΡΡΠ°Π½ΡΡΡ Π· Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½ΡΠΌ Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Π΄Π»Ρ ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ Π΅Π½Π΅ΡΠ³ΠΎΡΠΏΠΎΠΆΠΈΠ²Π°Π½Π½Ρ ΡΠ° ΡΠΎΠ·ΠΏΠΎΠ΄ΡΠ»Ρ ΡΠ΅ΡΡΡΡΡΠ². ΠΠ±ΠΎΠ²'ΡΠ·ΠΊΠΈ: Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΡΠ° Π½Π°Π²ΡΠ°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ...ΠΡΡΠ°Ρ! Π¨ΡΠΊΠ°ΡΠΌΠΎ Π΄ΠΎΡΠ²ΡΠ΄ΡΠ΅Π½ΠΎΠ³ΠΎ Data Scientist/ML Engineer Π΄Π»Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΡΡΡΠ΅Π½Ρ Π΄Π»Ρ Π²ΡΡΡΡΠ°Π»ΡΠ½ΠΎΡ Π΅Π»Π΅ΠΊΡΡΠΎΡΡΠ°Π½ΡΡΡ Π· Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½ΡΠΌ Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Π΄Π»Ρ ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ Π΅Π½Π΅ΡΠ³ΠΎΡΠΏΠΎΠΆΠΈΠ²Π°Π½Π½Ρ ΡΠ° ΡΠΎΠ·ΠΏΠΎΠ΄ΡΠ»Ρ ΡΠ΅ΡΡΡΡΡΠ².
ΠΠ±ΠΎΠ²'ΡΠ·ΠΊΠΈ:
- Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΡΠ° Π½Π°Π²ΡΠ°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ Π΄Π»Ρ Π°Π½Π°Π»ΡΠ·Ρ ΡΠ°ΡΠΎΠ²ΠΈΡ ΡΡΠ΄ΡΠ² Ρ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΡΠ²Π°Π½Π½Ρ
- ΠΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ Π΅Π½Π΅ΡΠ³Π΅ΡΠΈΡΠ½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ Π΄Π°Π½ΠΈΡ
- ΠΠ½ΡΠ΅Π³ΡΠ°ΡΡΡ ML-Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ² Ρ ΠΌΠ°ΡΡΡΠ°Π±ΠΎΠ²Π°Π½Ρ ΡΠΈΡΡΠ΅ΠΌΠΈ
- Π ΠΎΠ±ΠΎΡΠ° Π· Ρ ΠΌΠ°ΡΠ½ΠΈΠΌΠΈ ΡΠ΅ΡΠ²ΡΡΠ°ΠΌΠΈ ΡΠ° MLOps-ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ
- Π‘ΠΏΡΠ²ΠΏΡΠ°ΡΡ Π· ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ ΡΠΎΠ·ΡΠΎΠ±Π½ΠΈΠΊΡΠ² Π΄Π»Ρ Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ
ΡΡΡΠ΅Π½Ρ
ΠΠΈΠΌΠΎΠ³ΠΈ:
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Data Scientist / ML Engineer Π²ΡΠ΄ 2 ΡΠΎΠΊΡΠ²
- ΠΠΏΠ΅Π²Π½Π΅Π½Π΅ Π²ΠΎΠ»ΠΎΠ΄ΡΠ½Π½Ρ Python:
- NumPy, Pandas, Scikit-learn Π΄Π»Ρ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ ΡΠ° Π°Π½Π°Π»ΡΠ·Ρ Π΄Π°Π½ΠΈΡ
- Matplotlib, Seaborn, Plotly Π΄Π»Ρ Π²ΡΠ·ΡΠ°Π»ΡΠ·Π°ΡΡΡ
- TensorFlow/PyTorch Π΄Π»Ρ Π³Π»ΠΈΠ±ΠΎΠΊΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ
- XGBoost/LightGBM Π΄Π»Ρ Π°Π½ΡΠ°ΠΌΠ±Π»Π΅Π²ΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΡΠ²
- Prophet, ARIMA/SARIMA Π΄Π»Ρ ΡΠ°ΡΠΎΠ²ΠΈΡ ΡΡΠ΄ΡΠ²
- ΠΡΠ°ΠΊΡΠΈΡΠ½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ Π· Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°ΠΌΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΡΠ²Π°Π½Π½Ρ ΡΠ°ΡΠΎΠ²ΠΈΡ ΡΡΠ΄ΡΠ²
- ΠΠ°Π²ΠΈΡΠΊΠΈ ΡΠΎΠ±ΠΎΡΠΈ Π· AWS:
- AWS SageMaker Π΄Π»Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΡΠ° ΡΠΎΠ·Π³ΠΎΡΡΠ°Π½Π½Ρ ML-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
- AWS Timestream Π΄Π»Ρ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ°ΡΠΎΠ²ΠΈΠΌΠΈ ΡΡΠ΄Π°ΠΌΠΈ
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠΈΠ½ΡΠΈΠΏΡΠ² ΡΠΎΠ±ΠΎΡΠΈ Π· Π²Π΅Π»ΠΈΠΊΠΈΠΌΠΈ ΠΎΠ±ΡΡΠ³Π°ΠΌΠΈ Π΄Π°Π½ΠΈΡ
- ΠΠΎΡΠ²ΡΠ΄ Π· ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ:
- Git Π΄Π»Ρ Π²Π΅ΡΡΡΠΎΠ½ΡΠ²Π°Π½Π½Ρ ΠΊΠΎΠ΄Ρ
- Docker Π΄Π»Ρ ΠΊΠΎΠ½ΡΠ΅ΠΉΠ½Π΅ΡΠΈΠ·Π°ΡΡΡ
- Airflow/Luigi Π΄Π»Ρ ΠΎΡΠΊΠ΅ΡΡΡΠ°ΡΡΡ ΠΏΠΎΡΠΎΠΊΡΠ² Π΄Π°Π½ΠΈΡ
- MLflow Π΄Π»Ρ ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΆΠΈΡΡΡΠ²ΠΈΠΌ ΡΠΈΠΊΠ»ΠΎΠΌ ML-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ- Π ΠΎΠ±ΠΎΡΡ Π½Π°Π΄ ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΈΠΌ ΠΏΡΠΎΡΠΊΡΠΎΠΌ Ρ Π·ΡΠΎΡΡΠ°ΡΡΡΠΉ Π³Π°Π»ΡΠ·Ρ
- ΠΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΎΠ³ΠΎ ΡΠΎΠ·Π²ΠΈΡΠΊΡ ΡΠ° Π½Π°Π²ΡΠ°Π½Π½Ρ
- ΠΠ½ΡΡΠΊΠΈΠΉ Π³ΡΠ°ΡΡΠΊ ΡΠΎΠ±ΠΎΡΠΈ
- ΠΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½Ρ Π·Π°ΡΠΎΠ±ΡΡΠ½Ρ ΠΏΠ»Π°ΡΡ ΡΠ° Π±ΠΎΠ½ΡΡΠΈ
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Β· 52 views Β· 2 applications Β· 11d
Machine Learning Engineer
Countries of Europe or Ukraine Β· 2 years of experience Β· Upper-IntermediateAbout us: Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 8 years, we have...About us:
More
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 8 years, we have diligently fostered the largest Data Science Community in Eastern Europe.
About the project:
The project deals with financial forecasts, harness technology, data analytics, and deep market insights to deliver attractive, risk-adjusted returns for investors, regardless of market cycles or phases.
About the role:
We are looking for a Machine Learning Engineer to join the team.
Requirements:
- 2+ years of experience as a Machine Learning Engineer.
- Experience of working with time series, LSTM, Arima, and Gradient Boosting.
- Previous experience of working in the fintech is a must.
- BS/MS in AI, Computer Science, Mathematics, or related field.
- Expertise in statistical modeling and quantitative analysis.
- Experience with big data frameworks (e.g., Apache Spark, Hadoop) and real-time data streaming technologies (e.g., Kafka).
- Proven experience of working with data visualization (e.g., Matplotlib, PowerBI, Tableau).
- Previous experience working with core libraries: TensorFlow, PyTorch, Scikit-learn, and Statsmodels.
- Strong hands-on experience with Pandas, NumPy, SciPy, TA-Lib, PyWavelets, pykalman.
- Excellent knowledge of PostgreSQL, S3/GCS, MLFlow, Ray Tune/Optuna.
- Experience of working with Cloud Services: AWS/GCP/Azure.
Would be a plus:
- Understanding of trading principles, market microstructure, algorithmic trading strategies, and various financial instruments (stocks, indices, ETFs, commodities).
- Experience with developing and implementing trading strategies, portfolio management, and risk management techniques.
- Understanding of overfitting issues and knowing how to deal with that and walk-forward testing, k-fold cross-validation.
- Ability to translate complex analytical findings into trading decisions for both technical and non-technical colleagues.
- Expertise in simulation techniques, ensuring strategies are validated against realistic market conditions.
We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits youβll find out at the interview. -
Β· 95 views Β· 6 applications Β· 11d
Middle Data Scientist (classic modeling)
Ukraine Β· Product Β· 1 year of experience Β· Beginner/ElementaryΠΡΠΈΠ²Π°Ρ ΠΠ°Π½ΠΊ β Ρ Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΈΠΌ Π±Π°Π½ΠΊΠΎΠΌ Π£ΠΊΡΠ°ΡΠ½ΠΈ ΡΠ° ΠΎΠ΄Π½ΠΈΠΌ Π· Π½Π°ΠΉΠ±ΡΠ»ΡΡ ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΈΡ Π±Π°Π½ΠΊΡΠ² ΡΠ²ΡΡΡ. ΠΠ°ΠΉΠΌΠ°Ρ Π»ΡΠ΄ΠΈΡΡΡΡΡ ΠΏΠΎΠ·ΠΈΡΡΡ Π·Π° Π²ΡΡΠΌΠ° ΡΡΠ½Π°Π½ΡΠΎΠ²ΠΈΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π½ΠΈΠΊΠ°ΠΌΠΈ Π² Π³Π°Π»ΡΠ·Ρ ΡΠ° ΡΠΊΠ»Π°Π΄Π°Ρ Π±Π»ΠΈΠ·ΡΠΊΠΎ ΡΠ²Π΅ΡΡΡ Π²ΡΡΡΡ Π±Π°Π½ΠΊΡΠ²ΡΡΠΊΠΎΡ ΡΠΈΡΡΠ΅ΠΌΠΈ ΠΊΡΠ°ΡΠ½ΠΈ. ΠΠΈ ΡΡΠΊΠ°ΡΠΌΠΎ Data scientist Ρ Data...ΠΡΠΈΠ²Π°Ρ ΠΠ°Π½ΠΊ β Ρ Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΈΠΌ Π±Π°Π½ΠΊΠΎΠΌ Π£ΠΊΡΠ°ΡΠ½ΠΈ ΡΠ° ΠΎΠ΄Π½ΠΈΠΌ Π· Π½Π°ΠΉΠ±ΡΠ»ΡΡ ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΈΡ Π±Π°Π½ΠΊΡΠ² ΡΠ²ΡΡΡ. ΠΠ°ΠΉΠΌΠ°Ρ Π»ΡΠ΄ΠΈΡΡΡΡΡ ΠΏΠΎΠ·ΠΈΡΡΡ Π·Π° Π²ΡΡΠΌΠ° ΡΡΠ½Π°Π½ΡΠΎΠ²ΠΈΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π½ΠΈΠΊΠ°ΠΌΠΈ Π² Π³Π°Π»ΡΠ·Ρ ΡΠ° ΡΠΊΠ»Π°Π΄Π°Ρ Π±Π»ΠΈΠ·ΡΠΊΠΎ ΡΠ²Π΅ΡΡΡ Π²ΡΡΡΡ Π±Π°Π½ΠΊΡΠ²ΡΡΠΊΠΎΡ ΡΠΈΡΡΠ΅ΠΌΠΈ ΠΊΡΠ°ΡΠ½ΠΈ.
ΠΠΈ ΡΡΠΊΠ°ΡΠΌΠΎ Data scientist Ρ Data Π΄ΠΈΡΠ΅ΠΊΡΡΡ Π±Π°Π½ΠΊΡ, ΡΠΊΠΈΠΉ ΠΏΡΠ°Π³Π½Π΅ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π² Π΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΎΠΌΡ ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΡ ΡΠ° ΡΠΎΠ·Π΄ΡΠ»ΡΡ ΡΡΠ½Π½ΠΎΡΡΡ Π²Π·Π°ΡΠΌΠ½ΠΎΡ Π΄ΠΎΠ²ΡΡΠΈ, Π²ΡΠ΄ΠΊΡΠΈΡΠΎΡΡΡ ΡΠ° ΡΠ½ΡΡΡΠ°ΡΠΈΠ²Π½ΠΎΡΡΡ.
ΠΠΈ ΠΏΡΠ°Π³Π½Π΅ΠΌΠΎ Π·Π½Π°ΠΉΡΠΈ ΡΡΠ»Π΅ΡΠΏΡΡΠΌΠΎΠ²Π°Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ½Π°Π»Π°, ΡΠΊΠΈΠΉ Π²ΠΌΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π² ΡΠ΅ΠΆΠΈΠΌΡ Π±Π°Π³Π°ΡΠΎΠ·Π°Π΄Π°ΡΠ½ΠΎΡΡΡ, ΠΎΡΡΡΠ½ΡΠΎΠ²Π°Π½ΠΎΠ³ΠΎ Π½Π° ΡΠΊΡΡΡΡ ΡΠ° ΡΠ΅Π·ΡΠ»ΡΡΠ°Ρ.
ΠΠ΅ΡΠ° ΠΏΠΎΡΠ°Π΄ΠΈ: Π°Π½Π°Π»ΡΠ· Π΄Π°Π½ΠΈΡ , ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²Π° ΡΠ° Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ML ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
ΠΡΠ½ΠΎΠ²Π½Ρ ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΈ:
- EDA
- ΠΠ±ΡΠΎΠ±ΠΊΠ°, ΠΎΡΠΈΡΠ΅Π½Π½Ρ ΡΠ° ΠΏΠ΅ΡΠ΅Π²ΡΡΠΊΠ° ΡΡΠ»ΡΡΠ½ΠΎΡΡΡ Π΄Π°Π½ΠΈΡ , ΡΠΎ Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΡΡΡ Π΄Π»Ρ Π°Π½Π°Π»ΡΠ·Ρ
- Π‘ΡΠ²ΠΎΡΠ΅Π½Π½Ρ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ Π²ΠΈΡΠ²Π»Π΅Π½Π½Ρ Π°Π½ΠΎΠΌΠ°Π»ΡΠΉ ΡΠ° ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ ΡΡ ΡΠΎΠ±ΠΎΡΠΈ
- Π‘ΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΡΠ° Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ML ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π΄Π»Ρ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ°Π±Π»ΠΈΡΠ½ΠΈΠΌΠΈ ΡΠ° Π½Π΅ΡΡΡΡΠΊΡΡΡΠΎΠ²Π°Π½ΠΈΠΌΠΈ Π΄Π°Π½ΠΈΠΌΠΈ (ΡΠ΅ΠΊΡΡ, Π·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½Π½Ρ, Π·Π²ΡΠΊ)
- Π‘Π΅Π³ΠΌΠ΅Π½ΡΠ°ΡΡΡ ΠΊΠ»ΡΡΠ½ΡΡΡΠΊΠΎΡ Π±Π°Π·ΠΈ
- ΠΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ ΠΏΡΠΎ ΡΠΎΠ·ΡΠΎΠ±ΠΊΡ ΡΠ° Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
- ΠΡΠ΅Π·Π΅Π½ΡΠ°ΡΡΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡΠ² Π·Π°ΠΌΠΎΠ²Π½ΠΈΠΊΠ°ΠΌ ΡΠ° ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π½ΠΈΠΊΠ°ΠΌ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠ΄ΡΠΎΠ·Π΄ΡΠ»ΡΠ²
ΠΡΠ½ΠΎΠ²Π½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ:
- ΠΠΈΡΠ° ΠΎΡΠ²ΡΡΠ°
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π½Π° ΠΏΠΎΠ·ΠΈΡΡΡ Data Scientist 1+ ΡΡΠΊ
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· SQL, Python
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ· ΡΠ°ΠΊΠΈΠΌΠΈ ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ ΡΠΊ: Classification, Regression, Clustering, Association Rule Learning, Anomaly Detection, Time series analysis
- ΠΠΎΡΠ²ΡΠ΄ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΡΠ° Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΠΏΠΎΠ²Π½ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Ρ ML ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ (from research to production)
- ΠΠΎΡΠ²ΡΠ΄ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΠΏΠΎΡΠΈΡΠ΅Π½ΠΈΡ DS ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΡΡΠ² (numpy, scipy, pandas, sklearn, xgboost, etc.)
- ΠΡΠ΄ΠΌΡΠ½Π½Π΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΡΠ² ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ ΡΠ° Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ²
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ ΡΠ°ΠΌΠΎΡΡΡΠΉΠ½ΠΎ ΡΠ° Π· ΡΠ»Π΅Π½Π°ΠΌΠΈ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ Π· ΡΡΠ·Π½ΠΈΠΌ Π±Π΅ΠΊΠ³ΡΠ°ΡΠ½Π΄ΠΎΠΌ
- Π£ΠΌΡΠ½Π½Ρ ΡΡΠ²ΠΎΡΡΠ²Π°ΡΠΈ Ρ ΠΏΡΠ΄ΡΡΠΈΠΌΡΠ²Π°ΡΠΈ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ ΠΏΡΠΎ ΡΡΠ²ΠΎΡΠ΅Π½Ρ ΠΌΠΎΠ΄Π΅Π»Ρ Ρ ΠΏΡΠΎΡΠ΅ΡΠΈ
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ / ΡΠ΅ΠΎΡΡΡ ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎΡΡΡ, Π°Π½Π°Π»ΡΠ·Ρ Π΄Π°Π½ΠΈΡ , ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ
- ΠΠ½Π°Π½Π½Ρ BI ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡΠ², Π²ΠΌΡΠ½Π½Ρ Π±ΡΠ΄ΡΠ²Π°ΡΠΈ Π΄Π°ΡΠ±ΠΎΡΠ΄ΠΈ Π΄Π»Ρ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ ΡΠΎΠ±ΠΎΡΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ
- ΠΠ΄Π°ΡΠ½ΡΡΡΡ Π±ΡΠ΄ΡΠ²Π°ΡΠΈ Π·ΠΌΡΡΡΠΎΠ²Π½Ρ Π²ΡΠ·ΡΠ°Π»ΡΠ·Π°ΡΡΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡΠ²
ΠΡΠ΄Π΅ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ: Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°ΡΡΠΉΠ½ΠΈΠΌΠΈ ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ, Π·Π°Π΄Π°ΡΠ°ΠΌΠΈ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ°ΡΡΡ, GenAI, Natural Language Processing
Π‘Π²ΠΎΡΠΌ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΠ°ΠΌ ΠΌΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- Π ΠΎΠ±ΠΎΡΡ Π² Π½Π°ΠΉΠ±ΡΠ»ΡΡΠΎΠΌΡ ΡΠ° ΡΠ½Π½ΠΎΠ²Π°ΡΡΠΉΠ½ΠΎΠΌΡ Π±Π°Π½ΠΊΡ Π£ΠΊΡΠ°ΡΠ½ΠΈ
- ΠΡΡΡΡΠΉΠ½Π΅ ΠΏΡΠ°ΡΠ΅Π²Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΡΠ° 24 ΠΊΠ°Π»Π΅Π½Π΄Π°ΡΠ½ΠΈΡ Π΄Π½Ρ Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ
- ΠΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ Π»ΡΠΊΠ°ΡΠ½ΡΠ½ΠΈΡ Ρ ΠΏΠΎΠ²Π½ΠΎΠΌΡ ΠΎΠ±ΡΡΠ·Ρ
- ΠΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½Ρ Π·Π°ΡΠΎΠ±ΡΡΠ½Ρ ΠΏΠ»Π°ΡΡ
- ΠΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ ΡΠ° ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΈΠΉ ΠΌΠΎΠ±ΡΠ»ΡΠ½ΠΈΠΉ Π·Π²βΡΠ·ΠΎΠΊ
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π΅ Π½Π°Π²ΡΠ°Π½Π½Ρ
- ΠΡΠ΄Π΄Π°Π»Π΅Π½Ρ ΡΠΎΠ±ΠΎΡΡ Π°Π±ΠΎ ΡΡΡΠ°ΡΠ½Ρ ΠΎΡΡΡΠΈ Π² ΠΠΈΡΠ²Ρ, ΠΠ½ΡΠΏΡΡ ΡΠ° ΠΡΠ²ΠΎΠ²Ρ, ΠΎΡΠ½Π°ΡΠ΅Π½Ρ Π³Π΅Π½Π΅ΡΠ°ΡΠΎΡΠ°ΠΌΠΈ ΡΠ° Starlink
ΠΡΠΈΠ²Π°ΡΠΠ°Π½ΠΊ Π²ΡΠ΄ΠΊΡΠΈΡΠΈΠΉ Π΄ΠΎ ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΈ ΡΠ° ΠΏΡΠ°ΡΠ΅Π²Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ Π²Π΅ΡΠ΅ΡΠ°Π½ΡΠ² i Π²Π΅ΡΠ΅ΡΠ°Π½ΠΎΠΊ, Π° ΡΠ°ΠΊΠΎΠΆ Π»ΡΠ΄Π΅ΠΉ Π· ΡΠ½Π²Π°Π»ΡΠ΄Π½ΡΡΡΡ.
ΠΠ»Ρ Π½Π°Ρ Π½Π΅ΠΏΡΠΈΠΉΠ½ΡΡΠ½ΠΎΡ Ρ Π΄ΠΈΡΠΊΡΠΈΠΌΡΠ½Π°ΡΡΡ ΡΠ΅ΡΠ΅Π· ΡΡΠ°Π½ Π·Π΄ΠΎΡΠΎΠ²βΡ ΡΠ° ΡΡΠ·ΠΈΡΠ½Ρ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ, Π²ΡΠΊ, ΡΠ°ΡΠΎΠ²Ρ ΡΠΈ Π΅ΡΠ½ΡΡΠ½Ρ Π½Π°Π»Π΅ΠΆΠ½ΡΡΡΡ, ΡΡΠ°ΡΡ Ρ ΡΡΠΌΠ΅ΠΉΠ½ΠΈΠΉ ΡΡΠ°Π½.
ΠΠΈ Π³ΠΎΡΠΎΠ²Ρ Π½Π°Π²ΡΠ°ΡΠΈ Π²Π΅ΡΠ΅ΡΠ°Π½ΡΠ² ΡΠ° ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΡΠ² Π· ΡΠ½Π²Π°Π»ΡΠ΄Π½ΡΡΡΡ Π±Π΅Π· Π΄ΠΎΡΠ²ΡΠ΄Ρ ΡΠΎΠ±ΠΎΡΠΈ Π² Π±Π°Π½ΠΊΡΠ²ΡΡΠΊΡΠΉ ΡΡΠ΅ΡΡ.
Π―ΠΊΡΠΎ Π²ΠΈ ΠΌΠ°ΡΡΠ΅ ΡΡΠ°ΡΡΡ Π»ΡΠ΄ΠΈΠ½ΠΈ Π· ΡΠ½Π²Π°Π»ΡΠ΄Π½ΡΡΡΡ Π°Π±ΠΎ Π²Π΅ΡΠ΅ΡΠ°Π½Π°, Π·Π²Π΅ΡΡΠ°ΠΉΡΠ΅ΡΡ. Π€Π°Ρ ΡΠ²ΡΡ ΠΡΠΈΠ²Π°ΡΠΠ°Π½ΠΊΡ Π½Π°Π΄Π°Π΄ΡΡΡ ΠΊΠΎΠ½ΡΡΠ»ΡΡΠ°ΡΡΡ Ρ ΡΡΠΏΡΠΎΠ²ΡΠ΄ ΡΠΏΡΠΎΠ΄ΠΎΠ²ΠΆ ΠΏΡΠΎΡΠ΅ΡΡ Π²ΡΠ΄Π±ΠΎΡΡ ΡΠ° ΠΏΡΡΠ»Ρ ΠΏΡΠ°ΡΠ΅Π²Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ.
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Β· 15 views Β· 1 application Β· 16d
Senior/Lead Game Mathematician (Slots)
Ukraine Β· Product Β· 4 years of experience Β· IntermediatePlatipus is looking for a talented Game Mathematician (Slots) to join our team. If you are passionate about creating mathematical models for games, analyzing gameplay, and balancing game mechanics, this position is for you! Requirements: 4+ years of...Platipus is looking for a talented Game Mathematician (Slots) to join our team. If you are passionate about creating mathematical models for games, analyzing gameplay, and balancing game mechanics, this position is for you!
Requirements:- 4+ years of experience as a Game Mathematician (or similar position) in the iGaming industry and/or slot games.
- Understanding of how slot games work and how to make game mechanics within desired game parameters (RTP, volatility, SD etc.);
- Have experience with C++/C#;
- Strong skills in Microsoft Excel;
- Understanding successful elements of slot games;
- Experience with developing and exploring innovative functionality of slot games.
Responsibilities:
- Model and tune mathematical models using Excel;
- Create quick prototypes to test game flow and game balancing;
- Test and verify accuracy of mathematical models via simulations;
- Analyze user feedback and game statistics and adjust the mathematical model and game design accordingly.
- Contribute original ideas to the game logic and game design team.
We offer:
- Medical insurance;
- Regular salary reviews and timely payments;
- Provision of necessary equipment for work as needed;
- Official employment as a private entrepreneur;
- Psychological support.
Professional development:
- Corporate English classes;
- Mentoring from experienced Team Leads;
- 50% reimbursement for courses/certifications/webinars, etc.;
- Development towards leadership positions within the company.
Work-life balance:
- Ability to work fully remotely;
- 20 working days of vacation;
- Days off on public holidays;
- Informal office meetings every month.
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Β· 62 views Β· 7 applications Β· 17d
Machine Learning Engineer
Ukraine Β· Product Β· 2 years of experience Β· IntermediateSamsung R&D Institute Ukraine is looking for a passionate and collaborative Machine Learning Engineer to join our team. As a member of our team, you will participate in research & development of solutions related to device input performed with a...Samsung R&D Institute Ukraine is looking for a passionate and collaborative Machine Learning Engineer to join our team.
As a member of our team, you will participate in research & development of solutions related to device input performed with a stylus.
Solutions in areas: handwriting, image processing, artistic input and other human-computer interaction scenarios.
It is a good opportunity to work on a product used by millions of customers around the world on the most advanced Samsung devices.Responsibilities:
- Full-cycle participation in machine learning R&D projects: from design and implementation to deployment into production and further support
- Conduct research to improve existing solutions and architectures
- Implement data pipelines (feature engineering, data preprocessing, collection, etc.)
Research activities and strategic prototyping for future solutions
Major requirements:
- Proficiency in modern machine learning frameworks (TensorFlow, PyTorch, NumPy)
- Strong background in Python language (2+ years)
- Solid knowledge of math and statistics
- Experience of developing training pipelines from scratch
- Experience of building data preprocessing pipelines (outliers detection, denoising, splitting, etc)
- Experience with low-resource datasets
Will be a plus:
- Expirience with training, distilation, finetuning LLMs
- Master/PhD in Computer Science or related field
- Experience in ML models deployment on Android (TFLite)
- Awareness of Android application development (Java, Kotlin)
- Experience and interest in academic research, papers
- ML/DL contests participation experience (ex.: Kaggle)
Working Conditions:
- employment β GIG contract
- remote work is possible as well as work in Kyiv office
Benefits:
- competitive salary, annual salary review, annual bonuses
- paid 28 work days of annual vacations and sick leaves
- opportunity to become an inventor of international patents with paid bonuses
- medical & life insurance for employees and their children
- paid lunches
- discounts to Samsung products, services
- regular education and self-development on internal courses and seminars
- hybrid work format, working in office is required for some tasks
ΠΡΠΎ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Samsung R&D Institute Ukraine
Samsung Research and Development Institute Ukraine (SR Ukraine) is one of the units of R&D infrastructure of Samsung Electronics. Our local directions cover R&D activities in such areas as computer vision, next generations of human-computer interfaces based on 3D graphics and recognition technologies; applications for creating and consuming new types of multi-media content; device-2-device and device-2-cloud convergence; information security; artificial intelligence; natural language processing (NLP); human computer interaction (HCI); information retrieval; computational intelligence.
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The main goal of the SRUKR is to provide next generation, adaptive, context-aware intelligent services for Samsung products and immersive serendipity across software and hardware eco-systems. We provide prototypes and new generation software development from scratch for embedded devices that gives a chance for Ukrainian engineers to work on technology of the future.
Company offers medical insurance, life insurance for our employees and their children, free lunches, English/Korean courses. Competitive salary; bonus system and effective talent development system for our employees, various learning workshops and trainings.
Ukrainian labor legislation guarantees (in particular, 24 calendar days of annual paid vacations; day-off on Ukrainian official holidays; paid sick leave, paid maternity leave).
Our company is an equal opportunity employer and welcomes application from all qualified candidates. The data provide will only be used for consideration of the applied position or other suitable position in Samsung Electronics Ukraine CΠΎmpany Ltd. Personal data collected will be used for recruitment purpose only.
In the whole process of recruitment, applicants should be careful not to infringe the trade secret of the company which they have been / were working for.
Please note that Samsung Electronics will never ask applicants to submit any personal documents or sensitive personal data to facilitate the recruitment process.
ΠΠ°Π΄ΡΠΈΠ»Π°ΡΡΠΈ ΡΠ²ΠΎΡ ΡΠ΅Π·ΡΠΌΠ΅, Π―, Π½Π°Π΄Π°Ρ Π’ΠΠ βΠ‘Π°ΠΌΡΡΠ½Π³ Π Π½Π ΠΠ½ΡΡΠΈΡΡΡ Π£ΠΊΡΠ°ΡΠ½Π°β (ΠΠΠ ΠΠΠ£ 44648330) (Π½Π°Π΄Π°Π»Ρ β βΠΠΎΠΌΠΏΠ°Π½ΡΡβ) ΠΏΡΠ°Π²ΠΎ Π½Π° Π·Π±ΡΡ ΡΠ° ΠΎΠ±ΡΠΎΠ±ΠΊΡ ΠΌΠΎΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΎΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ, Π° ΡΠ°ΠΌΠ΅ ΠΏΡΡΠ·Π²ΠΈΡΠ°, ΡΠΌβΡ ΡΠ° ΠΏΠΎ-Π±Π°ΡΡΠΊΠΎΠ²Ρ, Π΄Π°ΡΠ° Π½Π°ΡΠΎΠ΄ΠΆΠ΅Π½Π½Ρ, ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈΠΉ Π½ΠΎΠΌΠ΅Ρ ΡΠ΅Π»Π΅ΡΠΎΠ½Ρ, Π°Π΄ΡΠ΅ΡΡ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΡ ΠΏΠΎΡΡΠΈ (Π½Π°Π΄Π°Π»Ρ β βΠΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½Ρ Π΄Π°Π½Ρβ) ΡΠ· ΠΌΠ΅ΡΠΎΡ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΡΠΈΡ Π΄Π°Π½ΠΈΡ Π΄Π»Ρ ΠΏΠΎΡΡΠΊΡ ΡΠ° ΠΏΡΠ΄Π±ΠΎΡΡ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΡΠ² Π½Π° Π·Π°ΠΌΡΡΠ΅Π½Π½Ρ Π²Π°ΠΊΠ°Π½ΡΠ½ΠΈΡ ΠΏΠΎΡΠ°Π΄ ΠΠΎΠΌΠΏΠ°Π½ΡΡ, Π½Π°ΠΏΠΎΠ²Π½Π΅Π½Π½Ρ ΡΠ΅ΠΊΡΡΡΠΈΠ½Π³ΠΎΠ²ΠΎΡ Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ ΠΠΎΠΌΠΏΠ°Π½ΡΡ.
ΠΠ»Ρ ΡΡΠΎΠ³ΠΎ Π½Π°Π΄Π°Ρ ΠΠΎΠΌΠΏΠ°Π½ΡΡ ΠΏΡΠ°Π²ΠΎ:
o Π½Π° Π·Π±ΡΡ, Π·Π±Π΅ΡΠ΅ΠΆΠ΅Π½Π½Ρ, Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΠΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ ;
o Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΠΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Π΄Π»Ρ Π·Π²βΡΠ·ΠΊΡ Π·Ρ ΠΌΠ½ΠΎΡ ΡΠ° Π½Π°Π΄ΡΠΈΠ»Π°Π½Π½Ρ ΠΌΠ΅Π½Ρ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ ΠΏΡΠΎ Π²Π°ΠΊΠ°Π½ΡΡΡ (-ΡΡ) Π² ΠΠΎΠΌΠΏΠ°Π½ΡΡ;
o Π·Π±Π΅ΡΡΠ³Π°ΡΠΈ ΠΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½Ρ Π΄Π°Π½Ρ Π² ΡΠ΅ΠΊΡΡΡΠΈΠ½Π³ΠΎΠ²ΡΠΉ Π±Π°Π·Ρ Π΄Π°Π½ΠΈΡ ΠΠΎΠΌΠΏΠ°Π½ΡΡ ΠΏΡΠΎΡΡΠ³ΠΎΠΌ ΡΡΡΠΎΠΊΡ ΡΡΠ½ΡΠ²Π°Π½Π½Ρ ΡΠ°ΠΊΠΎΡ Π±Π°Π·ΠΈ;
o Π²ΠΈΠ΄Π°Π»Π΅Π½Π½Ρ ΠΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Π· ΡΠ΅ΠΊΡΡΡΠΈΠ½Π³ΠΎΠ²ΠΎΡ Π±Π°Π·ΠΈ Π΄Π°Π½ΠΈΡ ΠΠΎΠΌΠΏΠ°Π½ΡΡ Ρ Π±ΡΠ΄Ρ-ΡΠΊΠΈΠΉ ΡΠ°Ρ Π½Π° ΡΠΎΠ·ΡΡΠ΄ ΠΠΎΠΌΠΏΠ°Π½ΡΡ.
Π¦Ρ ΠΠ³ΠΎΠ΄Π° Ρ Π±Π΅Π·ΡΡΡΠΎΠΊΠΎΠ²ΠΎΡ ΡΠ° ΠΌΠΎΠΆΠ΅ Π±ΡΡΠΈ Π²ΡΠ΄ΠΊΠ»ΠΈΠΊΠ°Π½Π° ΠΌΠ½ΠΎΡ Π·Π° ΠΌΠΎΡΠΌ ΠΏΠΈΡΡΠΌΠΎΠ²ΠΈΠΌ Π·Π²Π΅ΡΠ½Π΅Π½Π½ΡΠΌ Π½Π° Π°Π΄ΡΠ΅ΡΡ Π’ΠΠ βΠ‘Π°ΠΌΡΡΠ½Π³Π Π½Π ΠΠ½ΡΡΠΈΡΡΡ Π£ΠΊΡΠ°ΡΠ½Π°β: 01032, ΠΌ. ΠΠΈΡΠ², Π²ΡΠ». ΠΠ΅ΡΡΠΌΠ°Π½Π° ΠΠ°Π²Π»Π° Π‘ΠΊΠΎΡΠΎΠΏΠ°Π΄ΡΡΠΊΠΎΠ³ΠΎ, 57 -
Β· 31 views Β· 2 applications Β· 19d
Senior Data Scientist
Ukraine, Poland Β· 4 years of experience Β· Upper-IntermediateRingier Data Technology Department is looking for a Senior Data Scientist to join our team. Our team leverages the latest models to predict financial figures or the best price for an advertisement, create user facing chatbots and much more applications....Ringier Data Technology Department is looking for a Senior Data Scientist to join our team.
Our team leverages the latest models to predict financial figures or the best price for an advertisement, create user facing chatbots and much more applications. Weβre also working with cutting-edge technologies, like LLMs, trying to create applications that will drastically increase the visibility of Ringierβs brands.
Requirements:
- Strong record in applying Machine Learning to real-world datasets in a productive environment and are familiar with the main ML frameworks (TensorFlow, Torch, XGBoost, LightGBM, ...).
- Strong experience in Python.
- Experience with LLMs and frameworks like Langchain. You know the best practices and keep following the field so that you use the latest ones.
- Deep knowledge of the latest advances in the NLP domain.
- Experience in software development and confidence in developing the full ML model.
lifecycle from research to production ensuring aspects such as reproducibility and.scalability (git, dvc, Docker, Amazon Web Services) is a plus. - (MS, Ph.D.) Degree in computer science, statistics, mathematics or a comparable degree program or equivalent work experience.
- Youβre a team player and at the same time can be independent and take responsibility for your tasks. Structured way of working and creativity complete your profile.
- Experience with Palantir Foundry is a plus.
- Full professional proficiency in English.
Ukrainian language Advanced or higher.
Responsibilities:
- Working with various datasets from different Ringier companies in different business divisions across publishing and marketplaces and in different regions across continents.
- Be responsible for choosing, improving, and applying various methods from statistics, machine, and deep learning technologies in order to solve business problems.
- the data of our users, their interests and online behavior as well as the data of the different Ringierβs business units in order to serve the business demands, and enable the future business models.
- Working closely with cross-functional teams to develop prototypes and products for cross-portfolio use cases.
- Communication and visualization of the value of data by describing the findings or the way how techniques work to both technical and non-technical audiences.
Keeping closely following research and engineering developments mostly in the NLP field, like HuggingFace, LLMs roll in the relevant technologies and methodologies to keep our modern technology landscape up to date.
We offer:
- Flexible working format - remote, office-based or flexible
- A competitive salary and good compensation package
- Personalized career growth
- Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
- Active tech communities with regular knowledge sharing
- Education reimbursement
- Memorable anniversary presents
- Corporate events and team buildings
- Other location-specific benefits
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Β· 25 views Β· 2 applications Β· 19d
Senior Machine Learning Engineer
Ukraine Β· Product Β· 5 years of experience Β· Upper-IntermediateZoral Labs, a leading provider of research and development to the software industry, is searching for Senior Machine Leaning Engineer to join its development center in remotely Requirements - MSc or PhD degree in Computer Science, Applied Math or...Zoral Labs, a leading provider of research and development to the software industry, is searching for Senior Machine Leaning Engineer to join its development center in remotely
Requirements
- MSc or PhD degree in Computer Science, Applied Math or related field background in Mathematics (linear algebra, discrete math, probability theory and statistics, optimization theory)
- 5+ years of experience in Software Engineering and ML
- algorithms and data structures knowledge (e.g. divide and conquer, graph algorithms, dynamic programming, stacks/queues, heaps)- NLP experience (text categorization, NER, parsing);
- classic ML algorithms and approaches expertise (e.g. logistic regression, regularization, xgboost, etc.);
- neural networks for image and/or sequence modelling experience (e.g. CNN, LSTM, Transformers);
- understanding of mathematical foundations of LLM;
- experience with finetuning and deploy private LLMs to solve specific business problems;
- strong knowledge of Python
- experience with Unix tools (e.g. bash scripting)
- self-sufficiency: being able to work and deliver with the minimal support required
- a proven track record of project implementation from PoC to production
- good spoken and written English (B2+)
Would be a plus
- experience with cloud platforms (e.g. GCP: Vertex AI, Cloud Storage or AWS: SageMaker, ECS, S3)
- experience with PostgreSQL database and good SQL knowledge
- experience with CI/CD practices- experience with OCR
- exposure to Finance domain
- experience with logic programming (e.g. Prolog) or functional programming languages
- knowledge of Computer Vision algorithms (object detection, recognition, feature extraction, matching, projective geometry)
- participant of Kaggle, math/coding competitions
Responsibilities
As a member of the Machine Learning team, you will participate in multiple projects related to improvement of business operational efficiency, automated processing of financial documents in various formats (Intelligent Document Processing) that includes structure recognition, document categorization and parsing, information extraction and question answering.
In particular you will:
- collaborate with business analysis, development, and operations teams;
- capture key business requirements in communication and cooperation with the key business stakeholders;
- develop document recognition/processing technology using cutting-edge approaches, including LLMs;
- analyze state-of-the-art papers, benchmark different approaches;
- develop of PoC (proof of concept) and demo prototypes to validate requirements and design;
- develop production-ready solutions in close cooperation with development team;We offer:
Attractive salary and good opportunities for career and personal development
Compensation package
Good opportunities for career and personal development
Office in a picturesque place
About projects:
We specialize in advanced software fields such as BI, Data Mining, Artificial Intelligence, Machine Learning (AI/ML), High Speed Computing, Cloud Computing, BIG Data, Predictive Analytics, Unstructured Data processing, Finance, Risk Management and Security.
Depending on the project, it can be consulting in data analysis and risk management, with customers geography stretching all over the world or creation of extensible decision engine services, data analysis and management solutions, real-time automatic data processing applications.
If you are excited about development of artificial intellect, behavior analysis data solutions, big data approach then we can give you an opportunity to reveal your talentsΠΡΠΎ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Zoral Labs
Zoral is a fintech software research and development company. We were founded in 2004.
We operate one of largest labs in Europe focused on Artificial Intelligence/Machine Learning (AI/ML), predictive systems for consumer/SME credit and financial products.
Our clients are based in USA, Canada, Europe, Africa, Asia, South America and Australia.
We are one of the worldβs leading companies in the use of unstructured, social, device, MNO, bureau and behavioral data, for real-time decisioning and predictive modeling.
Zoral software intelligently automates digital financial products.
Zoral produced the worldβs first, fully automated, STP consumer credit platforms.
We are based in London, New York and Berlin
Π‘Π°ΠΉΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ:
zorallabs.com/company
Π‘ΡΠΎΡΡΠ½ΠΊΠ° ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π½Π° DOU:
https://jobs.dou.ua/companies/zoral/
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Junior / Middle Data Scientist
Ukraine Β· Product Β· 1 year of experience Ukrainian Product πΊπ¦SKELAR β ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΠΉ venture builder, ΡΠΊΠΈΠΉ Π±ΡΠ΄ΡΡ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½Ρ tech-Π±ΡΠ·Π½Π΅ΡΠΈ. Π Π°Π·ΠΎΠΌ ΡΠ· ΠΊΠΎ-ΡΠ°ΡΠ½Π΄Π΅ΡΠ°ΠΌΠΈ Π·Π±ΠΈΡΠ°ΡΠΌΠΎ ΡΠΈΠ»ΡΠ½Ρ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, ΡΠΎΠ± ΠΏΠ΅ΡΠ΅ΠΌΠ°Π³Π°ΡΠΈ Π½Π° Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΈΡ ΡΠΈΠ½ΠΊΠ°Ρ . Π‘ΡΠΎΠ³ΠΎΠ΄Π½Ρ Π² SKELAR β Π΄Π΅ΡΡΡΠΎΠΊ Π±ΡΠ·Π½Π΅ΡΡΠ² Ρ ΡΡΠ·Π½ΠΈΡ Π½ΡΡΠ°Ρ Π²ΡΠ΄ EdTech Π΄ΠΎ SaaS. Π¦Π΅ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠΎ ΠΌΠ°ΡΡΡ...SKELAR β ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΠΉ venture builder, ΡΠΊΠΈΠΉ Π±ΡΠ΄ΡΡ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½Ρ tech-Π±ΡΠ·Π½Π΅ΡΠΈ. Π Π°Π·ΠΎΠΌ ΡΠ· ΠΊΠΎ-ΡΠ°ΡΠ½Π΄Π΅ΡΠ°ΠΌΠΈ Π·Π±ΠΈΡΠ°ΡΠΌΠΎ ΡΠΈΠ»ΡΠ½Ρ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, ΡΠΎΠ± ΠΏΠ΅ΡΠ΅ΠΌΠ°Π³Π°ΡΠΈ Π½Π° Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΈΡ ΡΠΈΠ½ΠΊΠ°Ρ .
Π‘ΡΠΎΠ³ΠΎΠ΄Π½Ρ Π² SKELAR β Π΄Π΅ΡΡΡΠΎΠΊ Π±ΡΠ·Π½Π΅ΡΡΠ² Ρ ΡΡΠ·Π½ΠΈΡ Π½ΡΡΠ°Ρ Π²ΡΠ΄ EdTech Π΄ΠΎ SaaS. Π¦Π΅ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠΎ ΠΌΠ°ΡΡΡ Π²ΡΠ΄Π·Π½Π°ΠΊΠΈ Π²ΡΠ΄ Product Hunt, ΠΏΠΎΡΡΠ°ΠΏΠ»ΡΡΡΡ Ρ ΡΠ΅ΠΉΡΠΈΠ½Π³ΠΈ Π’ΠΠ-ΡΡΠ°ΡΡΠ°ΠΏΡΠ² ΡΠ° ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ²ΠΈΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ Π£ΠΊΡΠ°ΡΠ½ΠΈ, Π·Π°ΠΉΠΌΠ°ΡΡΡ Π½Π°ΠΉΠ²ΠΈΡΡ ΡΠ°Π±Π»Ρ Π² AppStore ΡΠ° ΡΠΎΠ·ΡΠΎΠ±Π»ΡΡΡΡ ΠΏΠ»Π°ΡΡΠΎΡΠΌΠΈ, ΡΠΊΠΈΠΌΠΈ ΠΊΠΎΡΠΈΡΡΡΡΡΡΡΡ ΠΌΡΠ»ΡΠΉΠΎΠ½ΠΈ Π»ΡΠ΄Π΅ΠΉ. Π ΡΠ΅ ΠΏΡΠΎ Π±ΡΠ·Π½Π΅ΡΠΈ SKELAR ΠΏΠΈΡΡΡΡ TechCrunch, Wired ΡΠ° ΡΠ½ΡΡ ΡΠ²ΡΡΠΎΠ²Ρ ΠΌΠ΅Π΄ΡΠ°.
ΠΠΈΡΠ°ΡΠΌΠΎΡΡ ΡΠΈΠ»ΡΠ½ΠΎΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ ΡΠ· 800+ ΡΠ°Ρ ΡΠ²ΡΡΠ², ΡΠΊΡ ΠΌΠ°ΡΡΡ ΠΊΡΡΡΡ Π΅ΠΊΡΠΏΠ΅ΡΡΠΈΠ·Ρ ΠΉ Π°ΠΌΠ±ΡΡΠ½Ρ ΡΡΠ»Ρ. ΠΠ°ΡΡ Π»ΡΠ΄ΠΈ β Π½Π°ΠΉΡΡΠ½Π½ΡΡΠΈΠΉ Π°ΠΊΡΠΈΠ² ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠΎΠΆ ΠΌΠΈ ΠΎΠ±ΠΈΡΠ°ΡΠΌΠΎ Π±ΡΠ΄ΡΠ²Π°ΡΠΈ Π±ΡΠ·Π½Π΅ΡΠΈ ΡΠ°Π·ΠΎΠΌ Π· Π½Π°ΠΉΠΊΡΠ°ΡΠΈΠΌΠΈ ΡΠ°Π»Π°Π½ΡΠ°ΠΌΠΈ Π½Π° ΡΠΈΠ½ΠΊΡ.
ΠΠ°ΡΠ°Π· ΠΌΠΈ Ρ ΠΏΠΎΡΡΠΊΡ Data Scientist Ρ Π½Π°ΡΡ ΠΏΠΎΡΡΡΠ΅Π»ΡΠ½Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ TENTENS Tech.
TENTENS Tech β ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠ° IT-ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠΎ ΡΠΎΠ·ΡΠΎΠ±Π»ΡΡ ΠΏΠ»Π°ΡΡΠΎΡΠΌΠΈ Ρ ΡΡΠ΅ΡΡ ΡΡΡΡΠΌΡΠ½Π³Ρ ΡΠ° social discovery. ΠΠΎΠΌΠ°Π½Π΄Π° TENTENS Tech ΠΌΠ°Ρ Π΄ΠΎΡΠ²ΡΠ΄ ΡΡΠΏΡΡΠ½ΠΈΡ Π·Π°ΠΏΡΡΠΊΡΠ² Π΄Π΅ΡΡΡΠΊΡΠ² ΠΏΠ»Π°ΡΡΠΎΡΠΌ, ΡΠΊΠΈΠΌΠΈ ΠΊΠΎΡΠΈΡΡΡΡΡΡΡΡ ΠΌΡΠ»ΡΠΉΠΎΠ½ΠΈ Π»ΡΠ΄Π΅ΠΉ Π½Π° Π²ΡΡΡ ΠΊΠΎΠ½ΡΠΈΠ½Π΅Π½ΡΠ°Ρ ΡΠ²ΡΡΡ (ΠΎΠΊΡΡΠΌ ΠΠ½ΡΠ°ΡΠΊΡΠΈΠ΄ΠΈ, ΠΏΠΎΠΊΠΈ ΡΠΎ). Π ΡΠ»ΠΎΠ³Π°Π½ We donβt think limits Π²ΡΠ΄ΠΎΠ±ΡΠ°ΠΆΠ°Ρ ΡΠΊ ΡΡΡΠ°ΡΠ΅Π³ΡΡΠ½Π΅ ΠΌΠΈΡΠ»Π΅Π½Π½Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ, ΡΠ°ΠΊ Ρ ΠΌΠΎΡΠΈΠ²Π°ΡΡΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ Π·Π°Π²ΠΆΠ΄ΠΈ ΠΌΡΠ°ΡΠΈ Π΄Π°Π»Π΅ΠΊΠΎ Π·Π° Π³ΠΎΡΠΈΠ·ΠΎΠ½Ρ. ΠΠ°ΡΠΌΠΎ ΠΏΠΎΡΡΠΆΠ½Ρ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ Π°Π½Π°Π»ΡΡΠΈΠΊΠΈ Π· 20+ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΡΠ².
Π¨ΡΠΊΠ°ΡΠΌΠΎ: ΡΠ°Π»Π°Π½ΠΎΠ²ΠΈΡΠΎΠ³ΠΎ data scientist-Π° Π· Π΄ΠΎΡΠ²ΡΠ΄ΠΎΠΌ ΡΠΎΠ±ΠΎΡΠΈ ΡΡΠΊ+, ΡΠΊΠΈΠΉ full-time Π±ΡΠ΄Π΅ ΡΠ°Π·ΠΎΠΌ Π· ΠΊΠΎΠ»Π΅Π³Π°ΠΌΠΈ ΡΠΎΠ·ΡΠΎΠ±Π»ΡΡΠΈ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½Ρ ΠΌΠΎΠ΄Π΅Π»Ρ Π΄Π»Ρ ΠΏΠΎΡΡΠ΅Π± Π±ΡΠ·Π½Π΅ΡΡ Ρ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈ Π²ΠΆΠ΅ Π½Π°ΡΠ²Π½Ρ. Π£ Π²Π°Ρ Π±ΡΠ΄Π΅ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ ΡΠ· ΡΡΠ·Π½ΠΎΠΌΠ°Π½ΡΡΠ½ΠΈΠΌΠΈ ΡΠΈΠΏΠ°ΠΌΠΈ Π΄Π°Π½ΠΈΡ ΡΠ° ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ, Π·Π°ΡΡΠΎΡΠΎΠ²ΡΠ²Π°ΡΠΈ Π½ΠΎΠ²ΡΡΠ½Ρ ΠΏΡΠ΄Ρ ΠΎΠ΄ΠΈ Π² ΠΎΠ±Π»Π°ΡΡΡ AΠ ΡΠ° ΠΏΡΠΎΠΏΠΎΠ½ΡΠ²Π°ΡΠΈ Π½Π°ΠΉΠΊΡΠ°ΡΡ ΡΡΡΠ΅Π½Π½Ρ Π΄Π»Ρ ΠΏΠΎΡΡΠ΅Π± Π±ΡΠ·Π½Π΅ΡΡ.
Π―ΠΊΡ Π²ΠΈΠΊΠ»ΠΈΠΊΠΈ ΡΠ΅ΠΊΠ°ΡΡΡ Π½Π° ΡΠ΅Π±Π΅ Π² ΡΠΎΠ»Ρ Data Scientist:
β Π ΠΎΠ·Π²ΠΈΡΠΎΠΊ Π²ΠΆΠ΅ Π½Π°ΡΠ²Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρ ΡΡ ΡΠ΅ΡΠ²ΡΡΡΠ² (Π°Π½ΡΠΈΡΡΠΎΠ΄, ΠΎΡΡΠ½ΠΊΠ° ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³Ρ, ΠΌΠΎΠ΄Π΅ΡΠ°ΡΡΡ);
β Π‘ΠΏΡΠ²ΠΏΡΠ°ΡΡ Π· Π°Π½Π°Π»ΡΡΠΈΠΊΠ°ΠΌΠΈ, DE-ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΠ°ΠΌΠΈ ΡΠ° ΡΠ½ΡΠΈΠΌΠΈ ΡΠ½ΠΆΠ΅Π½Π΅ΡΠ°ΠΌΠΈ Π΄Π»Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ ΡΠΊΠ»Π°Π΄Π½ΠΈΡ ML-ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½ΡΠ²;
β End-to-end ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ° Ρ Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ Π½ΠΎΠ²ΠΈΡ ML-ΡΠ΅ΡΠ²ΡΡΡΠ²;
β ΠΠ°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ ΡΠΊΠΎΡΡΡ ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½ΡΠ² ΡΡΠ΅Π½ΡΠ²Π°Π½Π½Ρ ΡΠ° ΡΠ΅ΡΡΡΠ²Π°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
β Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° Ρ Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΡΠΈΡΡΠ΅ΠΌ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ ΡΠΎΠ±ΠΎΡΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
Π©ΠΎ Π΄Π»Ρ Π½Π°Ρ Π²Π°ΠΆΠ»ΠΈΠ²ΠΎ:
β ΠΠΏΠ΅Π²Π½Π΅Π½Π΅ Π²ΠΎΠ»ΠΎΠ΄ΡΠ½Π½Ρ SQL ΡΠ° Python;
β ΠΠΏΠ΅Π²Π½Π΅Π½Ρ Π·Π½Π°Π½Π½Ρ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, ΡΠ΅ΠΎΡΡΡ ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎΡΡΠ΅ΠΉ ΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ;
β ΠΠ½Π°Π½Π½Ρ ΠΊΠ»Π°ΡΠΈΡΠ½ΠΈΡ ML-Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ²;
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ML-ΡΡΠ΅ΠΉΠΌΠ²ΠΎΡΠΊΠ°ΠΌΠΈ ΡΠ° Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠ°ΠΌΠΈ Π΄Π»Ρ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ Π΄Π°Π½ΠΈΡ ;
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· GCP/Azure/AWS;
β ΠΠΎΡΠ²ΡΠ΄ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ Ρ ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΈ ΠΏΠ°ΠΉΠΏΠ»Π°ΠΉΠ½ΡΠ² ΡΡΠ΅Π½ΡΠ²Π°Π½Π½Ρ/ΡΠ΅ΡΡΡΠ²Π°Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ;
β ΠΠ½Π°Π½Π½Ρ Docker, ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ IaS;
β ΠΠΊΡΡΠ°ΡΠ½ΡΡΡΡ, ΡΠ²Π°Π³Π° Π΄ΠΎ Π΄Π΅ΡΠ°Π»Π΅ΠΉ, ΠΊΡΠΈΡΠΈΡΠ½Π΅ ΠΌΠΈΡΠ»Π΅Π½Π½Ρ;
β ΠΠΌΡΠ½Π½Ρ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π² ΠΊΠΎΠΌΠ°Π½Π΄Ρ.
SKELAR foundation β Π±Π»Π°Π³ΠΎΠ΄ΡΠΉΠ½ΠΈΠΉ ΡΠΎΠ½Π΄, ΡΡΠ²ΠΎΡΠ΅Π½ΠΈΠΉ ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΠ°ΠΌΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ. Π ΠΌΠ΅ΠΆΠ°Ρ ΡΠ½ΡΡΡΠ°ΡΠΈΠ²ΠΈ ΡΡΠ²ΠΎΡΡΡΠΌΠΎ ΡΠ° ΡΡΠ½Π°Π½ΡΡΡΠΌΠΎ ΠΏΡΠΎΡΠΊΡΠΈ, ΡΠΎ ΡΠΏΡΠΈΡΡΡΡ ΠΏΠΎΠ΄ΠΎΠ»Π°Π½Π½Ρ Π½Π°ΡΠ»ΡΠ΄ΠΊΡΠ² Π²ΡΠΉΠ½ΠΈ ΡΠ° Π²ΡΠ΄Π½ΠΎΠ²Π»Π΅Π½Π½Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ.
SKELAR β ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΠ΅ Π΄Π»Ρ ΡΠ°ΠΌΠΎΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ Π»ΡΠ΄Π΅ΠΉ, ΡΠΊΡ Π·Π΄Π°ΡΠ½Ρ ΡΡΠ²ΠΎΡΠΈΡΠΈ ΡΡΠΏΡΡΠ½Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ. ΠΠΈ ΡΠ°ΠΊΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π½Π°Π·ΠΈΠ²Π°ΡΠΌΠΎ the next big everything. ΠΡΡΠΈΠΌΠΎ Π² ΡΡ ΠΏΠΎΡΡΠΆΠ½ΡΡΡΡ ΡΠ° ΠΌΠ°ΡΡΡΠ°Π±.ΠΠΈ ΠΏΠ»Π°Π½ΡΡΠΌΠΎ ΠΉ Π½Π°Π΄Π°Π»Ρ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈ tech-Π±ΡΠ·Π½Π΅ΡΠΈ, ΠΏΡΠ΄ΠΊΠΎΡΡΠ²Π°ΡΠΈ Π³Π»ΠΎΠ±Π°Π»ΡΠ½Ρ ΡΠΈΠ½ΠΊΠΈ ΡΠ° ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π·Π°Π΄Π»Ρ ΠΏΠ΅ΡΠ΅ΠΌΠΎΠ³ΠΈ Π£ΠΊΡΠ°ΡΠ½ΠΈ πΊπ¦
ΠΠ»Ρ ΡΡΠΎΠ³ΠΎ ΡΡΠ²ΠΎΡΠΈΠ»ΠΈ Π²ΡΡ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ Π²ΡΠ΅ΡΠ΅Π΄ΠΈΠ½Ρ Π½Π°ΡΠΎΠ³ΠΎ Π²Π΅Π½ΡΡΡ Π±ΡΠ»Π΄Π΅ΡΠ°:
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β 8 ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΠΈΡ ΠΊΠΎΠΌΠ°Π½Π΄, ΡΠΊΡ Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°ΡΡΡ Π±ΡΠ·Π½Π΅ΡΠ°ΠΌ Π·Π°ΠΊΡΠΈΠ²Π°ΡΠΈ Π±ΡΠ΄Ρ-ΡΠΊΡ ΠΏΠΈΡΠ°Π½Π½Ρ: Π²ΡΠ΄ ΡΠ΅ΠΊΡΡΡΠΈΠ½Π³Ρ Ρ ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΠΉ Π΄ΠΎ ΡΡΠ½Π°Π½ΡΡΠ² ΡΠ° ΡΡΠΈΠ΄ΠΈΡΠ½ΠΈΡ ΠΏΠΈΡΠ°Π½Ρ;
β Π‘ΠΏΡΠ»ΡΠ½ΠΎΡΠ° ΡΠ°ΡΠ½Π΄Π΅ΡΡΠ², ΡΠΊΡ Π²ΠΆΠ΅ Π·Π°ΠΏΡΡΡΠΈΠ»ΠΈ Π½Π΅ ΠΎΠ΄ΠΈΠ½ Π±ΡΠ·Π½Π΅Ρ ΠΉ ΠΌΠΎΠΆΡΡΡ Π΄ΡΠ»ΠΈΡΠΈΡΡ ΠΏΡΠ°ΠΊΡΠΈΡΠ½ΠΈΠΌ Π΄ΠΎΡΠ²ΡΠ΄ΠΎΠΌ;
β ΠΠ½ΡΡΡΡΡΠ½Ρ ΠΊΠ»ΡΠ±ΠΈ Π·Π° ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΈΠΌΠΈ Π½Π°ΠΏΡΡΠΌΠΊΠ°ΠΌΠΈ: ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³, ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ°, ΡΡΠ½Π°Π½ΡΠΈ, ΡΠ΅ΠΊΡΡΡΠΈΠ½Π³;
β Π’ΡΠ΅Π½ΡΠ½Π³ΠΈ, ΠΊΡΡΡΠΈ, Π²ΡΠ΄Π²ΡΠ΄ΡΠ²Π°Π½Π½Ρ ΠΊΠΎΠ½ΡΠ΅ΡΠ΅Π½ΡΡΠΉ;
β ΠΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ, ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΈΠΉ Π»ΡΠΊΠ°Ρ.
ΠΠ°Π²Π°ΠΉ ΡΠ°Π·ΠΎΠΌ Π±ΡΠ΄ΡΠ²Π°ΡΠΈ the next big everything! -
Β· 53 views Β· 1 application Β· 23d
Senior Data Scientist (LLM)
Worldwide Β· Product Β· 5 years of experience Β· Intermediate Ukrainian Product πΊπ¦MacPaw is a software company that develops and distributes software for macOS and iOS. Today, we have 20 million active users across all our products. At MacPaw, we believe humans and technology can reach their greatest potential together. MacPaw is proud...MacPaw is a software company that develops and distributes software for macOS and iOS. Today, we have 20 million active users across all our products.
At MacPaw, we believe humans and technology can reach their greatest potential together.
MacPaw is proud to be Ukrainian. The support and development of Ukraine are significant parts of the companyβs culture. MacPaw gathers open-minded people who support each other and aspire to change the world around us.
Imagine working on an AI-powered macOS assistant that feels truly intuitive, smart, and seamlessly integrated into users' daily workflows. At MacPaw, weβre pushing LLM-powered agents to the next level, and we need a Senior Data Scientist to help us get there.
In this role, you wonβt just build modelsβyouβll shape the next generation of on-device AI, tuning LLMs to achieve SOTA performance, RAG pipelines, and intelligent agents for real-world applications. Youβll work with top Engineers and Scientists to bring cutting-edge NLP and ML capabilities directly to macOS users.
If youβre passionate about LLMs, AI agents, and making AI more accessible and powerful, this is your chance to be at the forefront of a game-changing innovation.
P.S. Here, you can learn more about our macOS AI assistant: https://en.ain.ua/2025/01/22/macpaw-prepares-to-launch-eney-ai-assistant/
In this role, you will:
- Fine-tune LLMs
- Develop and fine-tune LLM-based agents for local task execution
- Design and build advanced RAG (Retrieval-Augmented Generation) pipelines for improved information retrieval
- Lead general deep-learning training and experimental initiatives. Cooperate with and mentor students from top Ukrainian universities
- Apply classical NLP techniques (e.g., NER, POS tagging)
- Set up a testing framework to evaluate agent performance, measure key metrics, and identify optimization opportunities
- Supervise macOS Engineers to integrate models on device
Skills youβll need to bring:
- Advanced experience in NLP and LLMs
- Proven ability to train custom NLP models and fine-tune pre-trained LLMs
- Strong background in Transformer architectures and their applications
- Proficiency in classical ML tasks (classification, regression, clustering)
- Experience with Python and NLP/ML frameworks (PyTorch, spaCy, NLTK, SciPy)
- Hands-on experience building LLM agents (RAG, ReAct, Plan&Execute, multi-agent systems)
- Good expertise in creating competitive advantage through LLM fine-tuning and RAG optimization
- Familiarity with LLM agent frameworks (LangChain, LangGraph, Vector Databases)
- Experience implementing metrics frameworks that align AI performance with business outcomes
At least an Intermediate level of English
- As a plus:
- Knowledge of running and optimizing open-source LLMs
- Background in conversational AI and dialog systems
- Familiarity with iOS/macOS ML frameworks for local deployment
- Experience with edge deployment of ML models
- Expertise with LangFuse or similar observability tools
What we offer:
- We are a Ukrainian company, and we stand with Ukraine against the russian aggression
We maintain workplaces for the mobilized Macpawians and provide financial support to colleagues or their families affected by the war. Here, you can also read about the MacPaw Foundation, which intends to help save the lives of Ukrainian defenders and provide relief to as many civilians as possible: https://macpaw.foundation/. - We are committed to our veterans
Our Veteran Career and Empowerment Program is designed to ensure our veterans and active military personnel receive the recognition, support, and opportunities they deserve. - Hybrid work model
Whether to work remotely or at the hub is entirely up to you. If you decide to mix it, our Kyiv office, which works as a coworking space, is open around the clock. The office is supplied with UPS and Starlink for an uninterrupted work process. - Your health always comes first
We guarantee medical insurance starting on your first working month. For those abroad, you can receive a yearly Medical insurance allowance as compensation for managing your medical expenses. - Flexible working hours
You can choose a schedule that is comfortable for you. No one here tracks your clock in/out because MacPaw is built on trust and cooperation. - Space to grow both professionally and personally
Education opportunities to grow both hard and soft skills, annual development reviews, and internal community. - Teams we are proud of
We build honest, transparent, and reliable relationships within teams. Every Macpawian can improve processes and implement their ideas. We encourage open and constructive feedback and provide training for Macpawians on giving and receiving feedback. - Office designed for people (and pets)
Our office has it all: a spacious workplace with enough room for sitting up, lying down, and running around; a gym for recreation; cozy kitchens; a sleeping/meditation room; and a terrace with a view where we throw summer parties. Also, we have two cats living in the office, and you are welcome to bring your pets to the office (we have separate floors for cats and dogs). - Time-off policy that covers lifeβs needs
Convenient personal time-off policy to help you take care of essential matters in your personal life, and parental leaves. On top of all that, sabbaticals are open after 5 years of being with MacPaw. - Join social initiatives with MacPawCares
MacPaw participates in numerous humanitarian aid and charity projects across many fields, and you are welcome to jump in to make the world a better place. - Weβre an equal-opportunity employer. Here is a safe place for applicants of all backgrounds
We are hiring talented humans. Meaning with all our variety of backgrounds and identities, including service members and veterans, women, members of the LGBTQIA+ community, individuals with disabilities, and other often underrepresented groups. MacPaw does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
*Some benefits are under development, and new adjustments are possible.
-
Β· 300 views Β· 18 applications Β· 24d
Junior Data Scientist
Office Work Β· Ukraine (Kyiv) Β· Product Β· 0.5 years of experienceΠΡΡΠ°ΡΠΌΠΎ Π² King Group ΠΌΡΡΡΡ, Π΄Π΅ Π·ΡΡΡΡΡΡΠ°ΡΡΡΡΡ Π½Π°ΠΉΠΊΡΠ°ΡΡ Π»ΡΠ΄ΠΈ Π· IT- ΡΠ° Π³Π΅ΠΌΠ±Π»ΡΠ½Π³-ΡΠ½Π΄ΡΡΡΡΡΡ, ΡΠΎΠ± ΡΠ°Π·ΠΎΠΌ ΡΠΎΠ±ΠΈΡΠΈ Π΄ΠΈΠ²ΠΎΠ²ΠΈΠΆΠ½Ρ ΡΠ΅ΡΡ. ΠΠΈ ΠΎΠΏΠ΅ΡΡΡΠΌΠΎ ΡΠΈΡΠ»Π΅Π½Π½ΠΈΠΌΠΈ ΠΏΡΠΎΡΠΊΡΠ°ΠΌΠΈ Ρ ΡΡΠ΅ΡΡ iGaming Π½Π° ΡΠΈΠ½ΠΊΠ°Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ, ΠΠ²ΡΠΎΠΏΠΈ ΡΠ° Π‘Π¨Π, ΡΠ½Π²Π΅ΡΡΡΡΠΌΠΎ Ρ Π²Π΅Π½ΡΡΡΠ½Ρ ΡΡΠ°ΡΡΠ°ΠΏΠΈ, ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½Ρ ΡΠ΄Π΅Ρ...ΠΡΡΠ°ΡΠΌΠΎ Π² King Group γΌ ΠΌΡΡΡΡ, Π΄Π΅ Π·ΡΡΡΡΡΡΠ°ΡΡΡΡΡ Π½Π°ΠΉΠΊΡΠ°ΡΡ Π»ΡΠ΄ΠΈ Π· IT- ΡΠ° Π³Π΅ΠΌΠ±Π»ΡΠ½Π³-ΡΠ½Π΄ΡΡΡΡΡΡ, ΡΠΎΠ± ΡΠ°Π·ΠΎΠΌ ΡΠΎΠ±ΠΈΡΠΈ Π΄ΠΈΠ²ΠΎΠ²ΠΈΠΆΠ½Ρ ΡΠ΅ΡΡ. ΠΠΈ ΠΎΠΏΠ΅ΡΡΡΠΌΠΎ ΡΠΈΡΠ»Π΅Π½Π½ΠΈΠΌΠΈ ΠΏΡΠΎΡΠΊΡΠ°ΠΌΠΈ Ρ ΡΡΠ΅ΡΡ iGaming Π½Π° ΡΠΈΠ½ΠΊΠ°Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ, ΠΠ²ΡΠΎΠΏΠΈ ΡΠ° Π‘Π¨Π, ΡΠ½Π²Π΅ΡΡΡΡΠΌΠΎ Ρ Π²Π΅Π½ΡΡΡΠ½Ρ ΡΡΠ°ΡΡΠ°ΠΏΠΈ, ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½Ρ ΡΠ΄Π΅Ρ ΡΠ° Π»ΡΠ΄Π΅ΠΉ.
ΠΠΈ Π°ΠΊΡΠΈΠ²Π½ΠΎ Π·ΡΠΎΡΡΠ°ΡΠΌΠΎ ΡΠ° ΡΠΎΠ·ΡΠΈΡΡΡΠΌΠΎΡΡ, ΡΡΠΏΡΡΠ½ΠΎ Π·Π°ΠΏΡΡΡΠΈΠ²ΡΠΈ ΡΠ° ΡΠΎΠ·ΡΠΈΡΠΈΠ²ΡΠΈ Π½ΠΈΠ·ΠΊΡ Π½ΠΎΠ²ΠΈΡ ΠΏΡΠΎΠ΄ΡΠΊΡΡΠ² ΠΏΡΠΎΡΡΠ³ΠΎΠΌ ΠΎΡΡΠ°Π½Π½ΡΠΎΠ³ΠΎ ΡΠΎΠΊΡ.
ΠΠ°ΡΠ°Π·Ρ ΠΌΠΈ Ρ ΠΏΠΎΡΡΠΊΠ°Ρ Junior Data Scientist, ΡΠΎ Π΄ΠΎΡΠ΄Π½Π°ΡΡΡΡΡ ΡΠ° ΠΏΡΠ΄ΡΠΈΠ»ΠΈΡΡ Π½Π°ΡΡ Analytics & Insights ΠΊΠΎΠΌΠ°Π½Π΄Ρ.
ΠΡΠΎ ΡΠΎΠ»Ρ: ΠΠΈ ΡΡΠΊΠ°ΡΠΌΠΎ ΡΠ°Π»Π°Π½ΠΎΠ²ΠΈΡΠΎΠ³ΠΎ ΡΠ° Π°ΠΌΠ±ΡΡΡΠΉΠ½ΠΎΠ³ΠΎ Junior Data Science Π½Π° ΠΏΠΎΠ²Π½ΠΈΠΉ ΡΠΎΠ±ΠΎΡΠΈΠΉ Π΄Π΅Π½Ρ Π΄Π»Ρ ΡΡΠ°ΡΡΡ Π² ΡΠ΅Π»Π΅Π½Π΄ΠΆΠΎΠ²ΠΈΡ iGaming ΠΏΡΠΎΡΠΊΡΠ°Ρ . ΠΠ°Ρ ΡΠ΄Π΅Π°Π»ΡΠ½ΠΈΠΉ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ - Π²ΠΌΠΎΡΠΈΠ²ΠΎΠ²Π°Π½ΠΈΠΉ, ΡΠ°ΠΌΠΎΡΡΡΠΉΠ½ΠΈΠΉ ΠΏΠΎΡΠ°ΡΠΊΡΠ²Π΅ΡΡ ΡΠ· ΡΠ΅Ρ Π½ΡΡΠ½ΠΎ ΡΠΈΠ»ΡΠ½ΠΈΠΌ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½ΠΈΠΌ Π±Π΅ΠΊΠ³ΡΠ°ΡΠ½Π΄ΠΎΠΌ.
ΠΡΠ½ΠΎΠ²Π½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ:
β Π‘ΡΡΠΏΡΠ½Ρ Π±Π°ΠΊΠ°Π»Π°Π²ΡΠ°/ΠΌΠ°Π³ΡΡΡΡΠ° Π°Π±ΠΎ Π΅ΠΊΠ²ΡΠ²Π°Π»Π΅Π½ΡΠ½ΠΈΠΉ Π΄ΠΎΡΠ²ΡΠ΄ Ρ Π³Π°Π»ΡΠ·Ρ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ, ΡΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΊΠΈ ΡΠΈ ΡΡΠΌΡΠΆΠ½ΠΈΡ Π³Π°Π»ΡΠ·Π΅ΠΉ;
β ΠΠ»ΠΈΠ±ΠΎΠΊΡ Π·Π½Π°Π½Π½Ρ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ ΡΠ° ΡΠ΅ΠΎΡΡΡ ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎΡΡΠ΅ΠΉ;
β ΠΠ°Π²ΠΈΡΠΊΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΡΠ²Π°Π½Π½Ρ Π½Π° Python;
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠ°ΠΌΠΈ: Pandas, Numpy, Scipy, Scikit-learn, Ρ ΡΠ΄.;
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ· SQL;
β ΠΠ»ΠΈΠ±ΠΎΠΊΠ΅ ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΊΠ»Π°ΡΠΈΡΠ½ΠΈΡ ML Π°Π»Π³ΠΎΡΠΈΡΠΌΡΠ²: Clustering, Logistic Regression, Decision Trees, Random Forest, Boostings.ΠΠ΄Π½ΠΎΠ·Π½Π°ΡΠ½ΠΎ Π±ΡΠ΄Π΅ Π²Π΅Π»ΠΈΠΊΠΎΡ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ:
More
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Time Series modeling;
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ DL framework: TensorFlow, PyTorch (+ CUDA);
β ΠΠΎΡΠ²ΡΠ΄ Π· GCP cloud: BigQuery, Cloud Functions.
Π’ΠΎΠ±Ρ ΡΠΎΡΠ½ΠΎ Π΄ΠΎ Π½Π°Ρ, ΡΠΊΡΠΎ ΡΠΈ:
β ΠΠΎΠ»ΠΎΠ΄ΡΡΡ Π²ΡΠ΄ΠΌΡΠ½Π½ΠΈΠΌΠΈ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΠΌΠΈ Π½Π°Π²ΠΈΡΠΊΠ°ΠΌΠΈ ΡΠ° ΠΊΡΠΈΡΠΈΡΠ½ΠΈΠΌ ΠΌΠΈΡΠ»Π΅Π½Π½ΡΠΌ;
β ΠΠ°ΡΡ ΡΠΈΠ»ΡΠ½Ρ ΠΎΡΠ³Π°Π½ΡΠ·Π°ΡΠΎΡΡΡΠΊΡ Π·Π΄ΡΠ±Π½ΠΎΡΡΡ;
β Π£Π²Π°ΠΆΠ½ΠΈΠΉ Π΄ΠΎ Π΄Π΅ΡΠ°Π»Π΅ΠΉ, Π° ΡΠ°ΠΊΠΎΠΆ ΠΌΠ°ΡΡ Π½Π°Π²ΠΈΡΠΊΠΈ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌ, ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΡΠ°ΡΠΎΠΌ Ρ Π»ΠΎΠ³ΡΠΊΠΈ;
β ΠΠ°ΡΡ ΠΆΠ°Π³Ρ Π΄ΠΎ ΡΡΠ·Π½ΠΎΠ³ΠΎ ΡΠΎΠ΄Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Ρ ΡΠ° ΡΠ°ΠΌΠΎΠ²Π΄ΠΎΡΠΊΠΎΠ½Π°Π»Π΅Π½Π½Ρ;
β ΠΠΎΠ»ΠΎΠ΄ΡΡΡ Π½Π°Π²ΠΈΡΠΊΠ°ΠΌΠΈ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡ ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΡΡ, Π·Π΄Π°ΡΠ½ΠΈΠΉ ΡΡΡΠΊΠΎ ΡΠ° Π»Π°ΠΊΠΎΠ½ΡΡΠ½ΠΎ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΡΠΈ Π΄Π°Π½Ρ ΠΊΠΎΠΌΠ°Π½Π΄Π°ΠΌ ΡΠ° Π·Π°ΡΡΠΊΠ°Π²Π»Π΅Π½ΠΈΠΌ ΡΡΠΎΡΠΎΠ½Π°ΠΌ.
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
β ΠΡΠ΄ΡΡΡΠ½ΡΡΡΡ Π±ΡΡΠΎΠΊΡΠ°ΡΡΡ Π² ΠΏΡΠΎΡΠ΅ΡΠ°Ρ ΠΏΡΠΈΠΉΠ½ΡΡΡΡ ΡΡΡΠ΅Π½Ρ Ρ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π±Π΅Π·ΠΏΠΎΡΠ΅ΡΠ΅Π΄Π½ΡΠΎ Π²ΠΏΠ»ΠΈΠ²Π°ΡΠΈ Π½Π° ΠΏΡΠΎΠ΄ΡΠΊΡ/ΠΏΡΠΎΡΠΊΡ;
β ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π½Π°Π²ΡΠ°ΡΠΈΡΡ β Π°Π±ΠΎ Π½Π°Π²ΡΠ°ΡΠΈ (ΠΌΠ°ΡΠΌΠΎ ΠΏΡΠΎΡΠΊΡΠΈ Π· ΡΠ½ΡΠ΅ΡΠ½Π°ΡΡΡΠΈ ΡΠ° ΠΌΠ΅Π½ΡΠΎΡΡΡΠ²Π°);
β Π Π΅Π°Π»ΡΠ·Π°ΡΡΡ ΡΠ΄Π΅ΠΉ ΡΠ΅ΡΠ΅Π· Π²Π»Π°ΡΠ½Ρ ΠΏΡΠΎΡΠΊΡΠΈ - ΠΠ΅ Π±ΡΠΉΡΠ΅ΡΡ Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡΠ²Π°ΡΠΈ! ΠΡΠΎΠΏΠΎΠ½ΡΠΉΡΠ΅ ΡΠ° ΠΎΠ²Π½Π΅ΡΡΡΡ ΠΏΡΠΎΡΠ΅Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ;
β ΠΡΠ΄ΡΡΠΈΠΌΡΡΡΠ΅ ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΠ΅ ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄Π°, ΡΠ· ΡΠΊΠΎΡ ΠΌΠΎΠΆΠ½Π° ΡΠΎΠ±ΠΈΡΠΈ Π΄ΡΠΉΡΠ½ΠΎ ΠΊΡΡΡΡ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈ, ΡΠΎ Π·ΠΌΡΠ½ΡΡΡΡ ΡΠΈΠ½ΠΎΠΊ;
β ΠΠ°ΡΠΏΠ»Π°ΡΡ ΡΡΠ²Π½Ρ IT-/iGaming-ΡΠΈΠ½ΠΊΡ ΡΠ° ΠΏΠΎΠ²Π½ΠΈΠΉ ΡΠΎΡΠΏΠ°ΠΊΠ΅Ρ (ΠΌΠ΅Π΄ΠΈΡΠ½Π° ΡΡΡΠ°Ρ ΠΎΠ²ΠΊΠ°, ΠΊΠΎΠ½ΡΡΠ»ΡΡΠ°ΡΡΡ ΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠ° Π² ΠΎΡΡΡΡ, ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ ΡΠΏΠΎΡΡΠ·Π°Π»Ρ, ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ Π²Π°ΡΡΠΎΡΡΡ Π»Π°Π½ΡΡΠ² Π· Π΄ΠΎΡΡΠ°Π²ΠΊΠΎΡ ΡΠΎΡΠΎ);
β ΠΡΡΡΠ½ΠΈΠΉ ΠΎΡΡΡ Ρ ΡΠ΅Π½ΡΡΡ ΠΠΈΡΠ²Π° (ΠΏΡΡΠΊΠΈ Π·Ρ ΠΠ²ΡΡΠΈΠ½Π΅ΡΡΠΊΠΎΡ/ΠΠΈΠ±ΡΠ΄ΡΡΠΊΠΎΡ) ΡΠ· Π·Π΅Π»Π΅Π½ΠΎΡ ΠΏΠ°Π½ΠΎΡΠ°ΠΌΠ½ΠΎΡ ΡΠ΅ΡΠ°ΡΠΎΡ. ΠΡΠΎΠ±Π»Π΅ΠΌΠ° Π±Π»Π΅ΠΊΠ°ΡΡΡΠ² Π²ΠΈΡΡΡΠ΅Π½Π° Π½Π° 100%;
β ΠΡΠ΄ΠΏΡΡΡΠΊΠ° - Ρ ΡΠ΅Π±Π΅ Π±ΡΠ΄Π΅ 17 ΡΠΎΠ±ΠΎΡΠΈΡ Π΄Π½ΡΠ² ΠΎΠΏΠ»Π°ΡΡΠ²Π°Π½ΠΎΡ Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ ΡΠ· Π½Π΅ΠΎΠ±ΠΌΠ΅ΠΆΠ΅Π½ΠΎΡ (ΠΌΠ°ΠΉΠΆΠ΅) ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π½Π°ΠΊΠΎΠΏΠΈΡΠ΅Π½Π½Ρ Π΄Π½ΡΠ² Π· ΠΌΠΈΠ½ΡΠ»ΠΎΠ³ΠΎ ΡΠΎΠΊΡ;
β ΠΠΊΡΡΡΠ°Π²ΠΈΡ ΡΠ΄Π½Ρ - Π² Π΅ΠΊΡΡΡΠ°Π΄Π½Ρ Π½Π°Π΄Π°ΡΠΌΠΎ Π΅ΠΊΡΡΡΠ°Π²ΠΈΡ ΡΠ΄Π½Ρ Π½Π°: ΠΎΠ΄ΡΡΠΆΠ΅Π½Π½Ρ, Π½Π°ΡΠΎΠ΄ΠΆΠ΅Π½Π½Ρ Π΄ΠΈΡΠΈΠ½ΠΈ, Π½Π΅ΠΏΠ΅ΡΠ΅Π΄Π±Π°ΡΡΠ²Π°Π½Ρ ΠΏΠΎΠ΄ΡΡ ΡΠ° ΡΠ½ΡΠ΅;
β ΠΠΎΠ½ΡΡ Π·Π° ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°ΡΡΡ - ΠΠΈ Π·Π°Π²ΠΆΠ΄ΠΈ ΡΠ°Π΄ΡΡΠΌΠΎ ΡΠ° ΡΡΠ½ΡΡΠΌΠΎ ΡΠ΅, ΡΠΎ ΡΡΠΌΠΌΠ΅ΠΉΡΠΈ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΡΡΡΡ ΡΠ²ΠΎΡΡ Π΄ΡΡΠ·ΡΠ², ΡΠΎΠΌΡ Π΄ΠΎ ΠΏΠ»ΡΡΡΠ² ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΏΠ΅ΡΠ΅Π²ΡΡΠ΅Π½ΠΎΡ ΡΠ° Π½Π°Π΄ΡΠΉΠ½ΠΎΡ Π»ΡΠ΄ΠΈΠ½ΠΎΡ ΠΌΠΈ Π΄ΠΎΠ΄Π°ΡΠΌΠΎ Π±ΠΎΠ½ΡΡ;
β Π Π΅Π»ΠΎΠΊΠ΅ΠΉΡ - Π·ΠΌΡΠ½Π° ΠΌΡΡΡΠ° ΠΏΡΠΎΠΆΠΈΠ²Π°Π½Π½Ρ Π·Π°Π²ΠΆΠ΄ΠΈ ΡΠΏΠΎΠ½ΡΠΊΠ°Ρ Π΄ΠΎ Π΄ΠΎΠ΄Π°ΡΠΊΠΎΠ²ΠΈΡ Π²ΠΈΡΡΠ°Ρ, Π° Π½Π°Ρ Π±ΠΎΠ½ΡΡ Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°Ρ ΠΏΡΠΎΠΉΡΠΈ ΡΠ΅ΠΉ ΠΏΠ΅ΡΡΠΎΠ΄ Π±Π΅Π· Π·Π°ΠΉΠ²ΠΈΡ ΡΡΡΠ΅ΡΡΠ².
Π―ΠΊΡΠΎ ΡΠΈ ΡΡΠΊΠ°ΡΡ Π΄Π»Ρ ΡΠ΅Π±Π΅ ΡΡΠ°Π±ΡΠ»ΡΠ½Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π· ΠΊΠ»Π°ΡΠ½ΠΈΠΌΠΈ Π»ΡΠ΄ΡΠΌΠΈ ΡΠ° ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΡΠΎΡΡΡ - ΡΠΎΠ±Ρ Π΄ΠΎ Π½Π°Ρ! ΠΡΠ΄ΠΏΡΠ°Π²Π»ΡΠΉ ΡΠ΅Π·ΡΠΌΠ΅! -
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Computer Vision Engineer
Office Work Β· Ukraine (Kyiv) Β· Product Β· 3 years of experience Β· Intermediate MilTech πͺEmployeer - defense tech company specializing in the development of innovative solutions in the direction of Embedded systems and radio frequency (RF) engineering. Responsibilities: β’β β Develop and implement computer vision algorithms using both...Employeer - defense tech company specializing in the development of innovative solutions in the direction of Embedded systems and radio frequency (RF) engineering.
Responsibilities:
β’β β Develop and implement computer vision algorithms using both classical techniques and neural networks
β’β β Utilize and understand popular networks and their building blocks in computer vision tasks
Requirements:
β’β β Proven experience with classical computer vision and neural networks
β’β β Strong understanding of geometrical computer vision principles
β’β β Hands-on experience in implementing low-level CV algorithms
β’β β In-depth knowledge of popular computer vision networks and components
β’β β Ability to quickly navigate through recent research and trends in computer vision
β’β β Proficiency in Python or C++
β’β β Experience with Linux
β’β β Extensive experience with common frameworks/libraries used for computer vision (OpenCV, numpy, PyTorch, ONNX, Eigen, etc.)
Working conditions:
- Full employment
- Work from the office in Kyiv
- Official employment
- Reservation from mobilization
- 24 calendar days of vacation and paid sick leave
- A dynamic, innovative and large-scale team working on a number of new products and improving current products
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