Senior Data Scientist

Automat-it

Що робити

Own Data Science projects end-to-end: Take customer problems from technical discovery through data analysis, solution design, experimentation, implementation, deployment, and production validation.
Choose the right technical approach: Evaluate whether a problem should be solved with prompt engineering, RAG, GenAI, agentic workflows, fine-tuning, smaller language models, classical ML, Computer Vision, recommendation systems, or custom model training.
Work deeply with data: Analyze and prepare customer datasets, identify data quality issues, create representative validation and golden datasets, and ensure the available data can support the chosen modelling approach.
Build and fine-tune ML models: Train, fine-tune, optimize, evaluate, and deploy models using Python, PyTorch/TensorFlow, SageMaker, and modern ML tooling.
Work with Generative AI: Build and evaluate GenAI solutions using Amazon Bedrock, RAG, prompt engineering, model selection, agentic workflows, and related AWS-native AI services.

5+ years of experience in Data Science, Machine Learning, Applied Science, or a closely related role.
Strong classical Machine Learning fundamentals and hands-on experience building production ML solutions.
Deep practical experience working with data, including data preparation, validation, feature engineering, dataset construction, and model evaluation.
Strong Python skills and hands-on experience with PyTorch and/or TensorFlow.
Strong practical experience with AWS SageMaker beyond notebook-level usage, including model training, deployment, inference, pipelines, or producti