Candidates 51
$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.
$5500 / mo
≈ $66000 / year net
Data Scientist / Data Engineer
Ukraine · 5 years of experience · Advanced/Fluent ·Published yesterday
Ukraine · 5 years of experience · Advanced/Fluent ·Published yesterday
- Image segmentation and object detection models (UNet, DeepLabV3+, YOLO, Vision Transformers, customized architectures, etc.)
- Transfer learning and semi-supervised learning techniques
- Classical image processing and preprocessing techniques: histograms, thresholding, edge detection, textural feature extraction, clustering, and distributions.
- Processing tabular data from various domains including finance, medical records, tests, and wearable devices.
- Machine learning algorithms: decision trees, random forests, XGBoost, Naive Bayes, SVM, linear models.
- Unsupervised learning methods: dimensionality reduction, clustering (e.g., Gaussian mixtures, k-means), distribution-based.
- Building ensemble models.
- Math, statistics.
- Science-based solutions.
- AWS, Serverless (Lambda, API Gateway, AppSync (GraphQL), RDS, Cassandra, VPC, EC2, Kinesis, Glue, Athena, SageMaker, DynamoDB, Comprehend etc.)
- Python (torch, tf, numpy, pandas, plotly, matplotlib, asyncio, sklearn, django, flask, ORMs).
Cloud Backend Engineer, Data Engineer | 2021-now
ONVY HealthTech
- Implemented algorithms and data pipelines for real-time data processing from various wearable devices (Garmin, Oura, Apple Watch, Polar, etc.) using ML for health management.
- Designed and implemented cloud infrastructures using Serverless, AWS and Python for efficient ETL processes and a robust application backend.
- Set up and managed data lakes and data streams.
Co-head of the Artificial Intelligence team. Deep Learning Engineer | 2019-now
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”
- Leveraged and created CV, ML and DL techniques for diagnosing tuberculosis, osteoporosis, infective endocarditis, and brain diseases in collaboration with the National Institute of phthisiology and pulmonology named after F.G. Yanovsky NAMS of Ukraine, Riga Stradinš University, The Heart Institute of Ukraine, Amosov National Institute of Cardiovascular Surgery, Romodanov Neurosurgery Institute NAMS of Ukraine.
- Processed military intelligence data from UAVs with CV, contributing to strategic decision-making and security operations.
Technical Team Lead. Cloud backend engineer | 2019-2021
2701323 Ontario Ltd
- Designed and built robust AWS cloud architectures for media-rich web application.
- Developed efficient backend systems to manage and process media content, with a focus on scalability and performance.
- Successfully led and managed a small technical team
- Developed and managed data pipelines and application backends to ensure efficient and scalable solutions.
- Experienced in working with various data types (images, tabular, etc.) in a variety of fields (healthcare, finance, military, etc.).
- Collaborated with leading medical institutes in Kiev to develop intelligent diagnostic systems based on computer vision.
- PhD student (Computer Science, Artificial Intelligence)
- Co-lead and core engineer of an AI-based R&D team at the main technical university of Ukraine
- 1st place in scientific research projects across Ukraine in the field of AI
$2500 / mo
≈ $30000 / year net
Machine Learning Engineer
Ukraine · Kyiv · 2.5 years of experience · Advanced/Fluent ·Published 24 April
Ukraine · Kyiv · 2.5 years of experience · Advanced/Fluent ·Published 24 April
- Auto Punctuation and Capitalization Service:
Tasks: Training and evaluating models, testing pre-trained models for punctuation and capitalization, optimizing and converting models for iOS deployment.
Technologies: Python, Pytorch, transformers, ONNX, coremltools, NLTK.
- RAG System Implementation:
Tasks: Enhancing OpenAI models through prompt fine-tuning to access external APIs.
Technologies: Python, langchain, FastAPI, MongoDB, OpenAI.
CV projects:
- 3D Feature Extraction Service:
Tasks: Stereo camera calibration, depth estimation, 3D feature extraction, API creation.
Technologies: Python, OpenCV, Flask.
- Barcode Reader Plugin for NX Witness:
Tasks: Developing a real-time detection system, optimizing object detection and OCR accuracy, managing model size, and deploying software.
Technologies: Python, paddlepaddle, C++, CMake, AWS, Flask.
14 weeks program gave me in-depth knowledge of Machine Learning methods and data processing.
Introduction to TensorFlow for Artificial Intelligence
Convolutional Neural Networks in TensorFlow
Machine Learning by Stanford University
Strategies to prevent overfitting.
Data Science Fundamentals
Pattern recognition.
March AI Hackathon
CSC Hackathon
Disinformation hackathon
$8000 / mo
≈ $96000 / year net
Software Engineer / Machine Learning Engineer
Ukraine · Kyiv · More than 10 years of experience · Advanced/Fluent ·Published 24 April · In passive search
Ukraine · Kyiv · More than 10 years of experience · Advanced/Fluent ·Published 24 April · In passive search
I have 9+ years of experience in IT in different roles: DevOps engineer (5 years), Python Back-end engineer (4 years), ML engineer (2+ years), Technical Lead (1 year). Such broad experience makes it possible for me to speak the same language with different engineers and understand them, which is very important while collaborating inside a team or a company. As an ML engineer, I'm able to not only train models in Jupyter notebook but also know how to convert business goals into technical tasks, design, and build the whole production system with ML models and surrounding infrastructure. Besides that, I have strong math and statistical background, and terms like "Central Limit Theorem", "p-value", "probability distribution" wouldn't scare me at all. I mean that I'm confident in doing complicated data analyses and sophisticated feature engineering.
I have experience in building two big software projects from scratch. One of them is the ML project, where I had a Tech Lead role (leading a team of 4 ML engineers). On that project, I designed the whole system (ML models, data pipelines, monitoring, analysis tools) and implemented it with the team from the first commit in git till the continuous deployments on production.
In my next journey, I was invited into a project in which research kind of work was already done and at that time we have to go into productions with a few hundred models. The main challenge was to organize previous research work in clean efficient production-ready code and set up engineering pipelines in a way, where we can simultaneously train dozens of models and receive feedback (performance metrics) as soon as possible. As a result, we decreased all models' training time from around 24 hours to 30 minutes.
The ideal management, for me, is clear, transparent, with common sense in the first place, without micro-management, time tracking, etc. I like when managers treat people as mature adult individuals and assess their work by the results.
Ideally, expect to have an opportunity with all above mentioned and where my broad experience is needed.
$4000 / mo
≈ $48000 / year net
ML Engineer
Ukraine · Kyiv · 4 years of experience · Advanced/Fluent ·Published 23 April
Ukraine · Kyiv · 4 years of experience · Advanced/Fluent ·Published 23 April
- End-to-end ML Engineering in automotive (vehicle test assistance app)
- AWS Ecosystem (Glue, SageMaker, Lambda etc.)
- GCP (BigQuery, GCC,
Python Stack: Pandas, NumPy, Flask, BeautifulSoup, Scrapy,
Selenium, Matplotlib, Seaborn, SQLAlchemy
ML Stack: Tensorflow, Keras, Scikit-learn, SciPy, XGBoost,
LightGBM
Dashboarding Stack: Tableau, Google Data Studio, Niche
Dashboarding
Databases: Oracle SQL, PostgreSQL, SQLite, BigQuery, MySQL
Notebooks: Jupyter Notebook, Google Colab
DevOps Stack: Docker, Google Cloud Composer, Terraform
Orchestrators Stack: Apache Airflow
AWS: SageMaker, Glue, Lambda, S3, SNS/SQS, ECR, ECS, RDS, EventBridge
- proven recommendation from Project Manager at Google
- proven as an independent combat unit at complex projects, which I handled for clients myself only
- developed a promotion algorithm which still serves the company faithfully for 3 years already
$1500 / mo
≈ $18000 / year net
Data Scientist
Ukraine · 2.5 years of experience · Advanced/Fluent ·Published 23 April
Ukraine · 2.5 years of experience · Advanced/Fluent ·Published 23 April
January 2023 – till now: Quantitative Analyst, Data Scientist - Data extraction and preparation, data fetching (API, Web Socket), Feature engineering, Quantitative analysis, strategy analysis, Time series predictive modeling. Models: SVM, Linear, Neural Networks (LSTM), Tree based (Random Forest). Instruments: Python, Pandas, NumPy, Scikit-Learn, TensorFlow.
October 2021 – till now: Developer/ Debugger at QualityUnit LLC – bug fixing, refactoring, database analysis, error logs analysis, Network communication analysis, designing solutions, adding functionality, customer communication. Tech stack: PHP 8.0, Javascript, MySql(MariaDB), Grafana, Kibana, Apache, Docker, Github, Intellij IDEA.
May 2021 – September 2021: PHP Web (Full-stack) Developer at TravelEarth agency – developing from scratch and deploying travel agency website; designing application and database. Tech stack: PHP, Javascript, HTML, CSS, MySql, Github.
2010 – 2012 : Postgraduate Course in Kyiv Shevchenko National University – Research on Game Theory and Economic Behavior of Counter-parties. Probability Theory and Mathematical Statistics, Fuzzy Sets, Game Theory.
-- ML Courses --
• Machine Learning with Python-From Linear Models to Deep Learning (Massachusetts Institute of Technology)
• Machine Learning with Python (freeCodeCamp)
-- Pet projects --
• Digital assets market analysis (Live) + Telegram bot alert-notifications
• Developing blog, using Vue.js / Node.js / Nest.js - Building REST API with authorization (JWT) and documented with Swagger. Based on Nest.js
-- Hobbies --
Market Analysis, investment, quantitative trading.
Data science - Quantitative analysis, Time series predictive modeling.
Programming: Python, PHP, Javascript
Math: Probability Theory, Statistics, Fuzzy Sets, Decision Making, Theory of Conflicts
Fluent English, Basic Spanish and Polish
Github:
.../serguzz/DataScience
.../serguzz
Data Science, Data Engineering
Machine Learning
Time series predictive modelling
Quantitative Analysis
$3000 / mo
≈ $36000 / year net
Data Scientist
Ukraine · 2 years of experience · Advanced/Fluent ·Published 23 April · In passive search
Ukraine · 2 years of experience · Advanced/Fluent ·Published 23 April · In passive search
Leading multiple analysis & econometric projects for local and international clients in FMCG, pharma, telecom & banking categories.
Experienced in data exploratory, statistical & regression analysis with ML methods: Marketing mix modeling, attribution & predictive modeling, scenario simulation for business in Python / R.
Building & supervising model development from scratch: from data collection and cleaning, feature engineering, choosing the most statistically appropriate method, hypothesis testing, validation of results to aligning with business context, and providing a report with outcomes & recommendations.
Modeling various KPIs that help clients better understand business performance, contribution of trade / media / other factors, optimize marketing mix & budgets to maximize ROI, sales.
Building predictive models to forecast KPI based on client's scenarios and provide recommendations on the optimal strategy to reach the target.
Introduced a new structure of Econometric department, leading organizational & methodological changes for increasing processes efficiency and communication with clients.
- Models created optimized trade and media strategy that led to increased revenue & ROI
- Accurately model category and brand development using predictive modeling
- Integrate tech & communication skills to find the balance between statistically precise / significant solution and shaping the outcomes in a relatable way efficiently communicating to senior stakeholders
$800 / mo
≈ $9600 / year net
Data scientist / NLP engineer
Ukraine · Kyiv · 1 year of experience · Advanced/Fluent ·Published 23 April
Ukraine · Kyiv · 1 year of experience · Advanced/Fluent ·Published 23 April
I have started by learning the basics of the NLP pipeline and gaining hands-on experience in data collection, labelling, preprocessing, feature engineering, topic modelling, text classification, clustering techniques, and quality metrics of a model.
I have advanced my expertise by learning the theoretical foundations of classic ML and Deep Learning, gaining comprehensive insights into the architecture of Neural Networks. The practical application of this knowledge was in building and training SimpleRNN and LSTM models for both binary and multi-label classification tasks.
Additionally, I got interested in applying Large Language Models (LLMs) to classify textual data and build AI-driven solutions.
- Engineered a prioritization system which aims to assist the customer support team in decreasing their response time to urgent situations and provides the marketing team with a summary of positive reviews.
- Initiated and led an AI chatbot project for language schools. Crafted a compelling pitch deck and presented the idea to a diverse group, receiving positive feedback.
What I value most in a workplace is the opportunity to gain hands-on experience through both independent tasks and in collaboration with more experienced colleagues.
I’m looking for a company which encourages continuous learning and participation in various hackathons and conferences
$4000 / mo
≈ $48000 / year net
Computational Linguist / NLP Specialist
Ukraine · Kyiv · 5 years of experience · Advanced/Fluent ·Published 23 April · In passive search
Ukraine · Kyiv · 5 years of experience · Advanced/Fluent ·Published 23 April · In passive search
$4500 / mo
≈ $54000 / year net
Data Scientist
Ukraine · Kyiv · 3 years of experience · Advanced/Fluent ·Published 23 April · In passive search
Ukraine · Kyiv · 3 years of experience · Advanced/Fluent ·Published 23 April · In passive search
- deep learning and classical machine learning approaches on tabular data for monthly revenue predictions, estimation of payment probabilities, client and portfolio scoring models
- work with SQL databases including data cleaning with tools for distributed computing (such as dask), exploratory data analysis, hypothesis testing and model selection (using tools such as ray)
- time-series modeling for history-aware deal-by-deal revenue prediction
- chat- and voice- bot models
- named-entity recognition for chatbots with transformers in English and Asian languages
- Voicebot, Speech-To-Text and Text-To-Speach web services
- Google Cloud services
- 8 peer-reviewed journal articles in high-energy physics
- 4 conference talks, multiple posters presented
- research-oriented tasks (more science, less engineering)
- flexible schedule