-
Languages & core
-
Python (Pandas, Polars, NumPy, Pydantic, FastAPI), SQL, Bash
- Data & cloud
-
Snowflake, dbt, Postgres, Spark / Databricks, AWS (S3, Batch,
Lambda, Step Functions, EventBridge Scheduler, CloudFormation),
Azure (AzureML, DevOps Pipelines, Application Insights), Docker,
Kubernetes, Datadog
- Machine learning
-
Scikit-learn, XGBoost, Prophet, BoTorch, Scikit-Optimize, MLflow
— statistical modelling, time-series forecasting, black-box
optimization, model calibration & evaluation
-
AI-assisted development
-
GitHub Copilot, Claude Code, Anthropic (Claude) and OpenAI models — code
migration, refactoring, test generation and day-to-day
development
-
Engineering practice
-
Unit & integration testing (Pytest), CI / CD, Git, MLOps,
monitoring & alerting, code review, refactoring and
stabilization of large code bases
- Ways of working
-
Agile team lead (SCRUM), requirement & stakeholder
management, project management, mentoring, presenting to
executive and non-technical audiences