Candidates 547
$5200 / mo
≈ $62400 / year net
Data Scientist, R programing, R+shiny programing
Ukraine · 6 years of experience · Upper-Intermediate ·Published today
Ukraine · 6 years of experience · Upper-Intermediate ·Published today
- Developing the hourly revenue prediction system and anomaly detection, real-time mode
- Developing the auto-bidding algorithm for the optimization of CAC and ROI (san, video
networks) - ad set/country/creative level
- Recommendation of best creatives for campaigns
- Deploying models to the production (R, Airflow, Docker, slack notifications)
- Detecting cheaters by analyzing dialogs using the ChatGPT API
- Developing an application for time series forecasting
- Developing of marketing waterfall model, ROI campaigns monitoring
- Development of scoring models (R, BigQuery, PostgreSQL) - Churn Rate, Conversion Rate, Active days prediction, etc.
- Development from scratch of the anomaly detection system (R package)
- Creation of automatic system for controlling main metrics of business departments (R, BigQuery, Shiny)
Development from scratch of the anomaly detection system (R package)
$5500 / mo
≈ $66000 / year net
Senior Android Developer
Ukraine · More than 10 years of experience · Upper-Intermediate ·Published today · In passive search
Ukraine · More than 10 years of experience · Upper-Intermediate ·Published today · In passive search
• Proficient in Kotlin and Java
• Kotlin Coroutines and Jetpack Compose
• API Protocols: REST, gRPC
• Version Control: GitHub, Bitbucket, GitLab
• Design patterns
• Interested in transitioning to an ML/AI role, with a particular focus on Computer Vision
Played a key role in developing Openpay's, a leading payments fintech in Australia, mobile application which helped the company go public with over 300k active users.
Contributed to the development of ironSource's mobile app Aura, which helps mobile operators increase revenue and helped the company to go public with over 8 million active users.
Helped develop the mobile application for Reface (AI Face Swap App), a well-known Ukrainian company with over 15 million active users.
$2700 / mo
≈ $32400 / year net
Data Scientist / Analyst / ML Researcher
Ukraine · Kyiv · 3 years of experience · Upper-Intermediate ·Published today
Ukraine · Kyiv · 3 years of experience · Upper-Intermediate ·Published today
Primary expertise: classical machine learning algorithms for regression, classification, clusterization problems, anomaly detection, dimensionality reduction, and time-series analysis.
Helped to increase the performance of existing models at previous work by up to 15 percentage points. Consolidated various data sources to provide a new fraud validation system. Successfully created an autoML scoring model and implemented it in production, which helped automate a significant part of the scoring analytics processes in the department of the previous company.
$8000 / mo
≈ $96000 / year net
Senior Data Engineer
Ukraine · 6 years of experience · Upper-Intermediate ·Published today · In passive search
Ukraine · 6 years of experience · Upper-Intermediate ·Published today · In passive search
- Spark Streaming applications
- Data lakes on AWS
$8000 / mo
≈ $96000 / year net
Senior/Lead Data Scientist/Machine Learning Developer
Ukraine · Kyiv · 10 years of experience · Advanced/Fluent ·Published today
Ukraine · Kyiv · 10 years of experience · Advanced/Fluent ·Published today
I have more than 9 years of software development experience (big corps & start ups) on roles related to machine learning, data science/engineering and R&D from scratch, last 4 years have been taking part in leading teams.
Looking for projects with real-world data and sensible business model involved in deep learning/machine learning and data streaming.
$5000 / mo
≈ $60000 / year net
Deep Learning Researcher
Ukraine · Kyiv · 3 years of experience · Intermediate ·Published today · In passive search
Ukraine · Kyiv · 3 years of experience · Intermediate ·Published today · In passive search
Innohub
• Сlustering of time series using autoencoders with recurrent neural networks and the attention
mechanism.
• Predicting car breakdown time using recurrent neural networks.
Machine learning researcher October 2021 - Present
Pawa
• Developed evolution algorithm for localizing objects on banner.
• Developed and trained model for video summarizing using pretrained image backbone and attention
layers.
• Created service for detecting real world and gameplay timings in video with zero-shot approach using
CLIP model.
• Trained few-shot segmentation model for video games domain.
• Implemented fine tuning method for few-shot segmentation model to increase metrics on subdomain.
• Created a method for selecting the best query set, which improved the performance of the few-shot
segmentation model.
• Created service for video deduplication and retrieval using self supervised video model and milvus vector
database.
• Created service for video shot boundary detection.
• Created service for interactive image segmentation using clicks and different types of input.
• Created service for long-term video object segmentation.
$5000 / mo
≈ $60000 / year net
Data Scientist
Azerbaijan · 6 years of experience · Advanced/Fluent ·Published today
Azerbaijan · 6 years of experience · Advanced/Fluent ·Published today
I have built the speech to text model for Azerbaijani language using dataset that we used crowdsourcing to gather.
Technologies used: kaldi, srilm, python, bash, pytorch, numpy, pandas
- Azerbaijani text to speech model:
I have built a text to speech model for Azerbaijani language using relatively clean utterances of two speakers. I used tacotron 2 and parallel wavegan models.
Tools used: python, pytorch, numpy, pandas,
- Media Monitoring project:
Wrote 200 crawlers to continuously grab news from 200 different news channels in Azerbaijan with a junior developer. Also applied generic crawlers to grab the news inside even if the html in the page changes.
Applied Similarity Detection on those news to get the unique news.
Applied Sentiment Analysis to classify those news as positive or negative.
Applied Text Classification to classify those news to different categories (Sport, Economics etc.)
Applied Named Entity Recognition to detect entities passing in the news to match them with the positive and negative news, so we can say that the name of this person or organisation is passing on negative news x% of the time.
Tools used: python, scikit, numpy, tensorflow, keras
Similarity detection, Named Entity Recognition, Sentiment Analysis, Text Classification. Tools used: python, scikit, numpy
2) I have built the first automatic media monitoring system for Azerbaijani, where I have applied, Named Entity Recognition, Sentiment Analysis, Text Classification, Keyword Extraction and Summarization.
$4200 / mo
≈ $50400 / year net
Data Scientist
Ukraine · Kremenchug · 3 years of experience · Upper-Intermediate ·Published today · In passive search
Ukraine · Kremenchug · 3 years of experience · Upper-Intermediate ·Published today · In passive search
Jun 2022 - Present (10 months)
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Lecturer IT STEP Computer Academy
Dec 2021 - Apr 2022 (5 months)
Lecturer in the discipline "Introduction to Microsoft Azure Cloud Technologies"
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Data Science RiverSoft
Aug 2021 - Apr 2022 (9 months)
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Data Science - Consultant RiverSoft
Dec 2020 - Aug 2021 (9 months)
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Back-end Developer - Consultant Hyuna International Ltd.
Jan 2019 - Aug 2021 (2 years 8 months)
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Full-stack web Developer LAMPDev
May 2018 - Dec 2018 (8 months)
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Дата присвоения звания июль 2020 г. Звание присвоено:Міністерство освіти і науки України Харківський національний університет радіоелектроніки
Публикации
1. Method of Classification of Tonal Estimations Time Series in Problems of Intellectual Analysis of Text
Content Method of Classification of Tonal Estimations Time Series in Problems of Intellectual Analysis
of Text Content
Transportation Research Procedia · Mar 20, 2020
2. Method for Evaluation the Pattern of Internet Service Customers Based on Stylometric Analysis
Oof their Text ContentMethod for Evaluation the Pattern of Internet Service Customers Based on
Stylometric Analysis Oof their Text Content
Proceedings of the 2022 IEEE 4th International Conference on Modern Electrical and Energy System,
MEES 2022 · Jan 16, 2023
$4500 / mo
≈ $54000 / year net
Data Scientist
Ukraine · Kyiv · 3 years of experience · Upper-Intermediate ·Published today
Ukraine · Kyiv · 3 years of experience · Upper-Intermediate ·Published today
I provide services such as data collection, data preprocessing, data analysis, building machine learning and deep learning models, and delivering results that can help derive insights for businesses from the data they have.
I have proven to be a data scientist who is enthusiastic about taking on new challenges
Predicted the top 20% of users that are prone to churn (it saved money to target only the high-risk consumers)
Created an automated data extraction solution that can be scaled to different markets regardless of their local data architecture for customer segmentation (it saved months for project scaling)
Provided the other types of insights answering some specific requests from markets (it saved weeks of investigation from the markets' side)
Prepared segmentation model for 10 markets, which enables further activation of 5 communication programs in the respective markets. The model outcome KPIs are used for more advanced tracking of market marketing activities
1. Interesting project/company where I can share my knowledge and improve my skills as a Data Scientist
2. To earn money is quite important. But for me is also important to deliver a high-quality service. Therefore, I want my work to be appreciated as it deserves
3. It's important for me to develop together with the people I work with so that we can share knowledge from different fields with each other (win-win strategy)
$3000 / mo
≈ $36000 / year net
Data Scientist
Ukraine · Ivano-Frankivsk · 3 years of experience · Pre-Intermediate ·Published today · In passive search
Ukraine · Ivano-Frankivsk · 3 years of experience · Pre-Intermediate ·Published today · In passive search
(dbt, SQL, BigQuery, Looker, Airflow, bash, Docker)
Time series forecasting with the addition of new fields from open sources. Experiments with boosting trees, neural networks, regression models and statistical methods. Model rolling into production and its support.
(pandas, numpy, LGBM, TensorFlow, plotly, matplotlib, open API)
Development of the intellectual part of the microservice for answers to questions on the company's internal documentation. The whole cycle of building a RAG system to improve model responses. Returning texts that were referenced in the answer, developing routings, adding dynamic data and function calls.
(OOP, FastAPI, Pinecone, PostgreSQL, GCP: VertexAI, AppEngine, cloud storage, cloud SQL)
Optimizing the work of genetic algorithms for solving tasks on a time matrix. Participating in pipeline development for comparing updated code with non-optimized code, writing to the repository and developing dashboards.
(numpy, numba, git, VMs, Genetic Algorithms)
1) AI assistant that understands language and talks to customers
2) AI assistant that can create documents using company templates
Our team showed determination and took third place