Alex Ostapenko

Data Scientist

Hi, I’m Alex! I’m a Data Scientist with a background in physics and over 4 years of research and industry experience in machine learning, software development, and large-scale data analysis. I hold an M.Sc. in Physics & Astronomy from the University of British Columbia, where I developed high-performance Python pipelines for large scientific datasets. My work focuses on machine learning, large-scale data processing, and building reliable data pipelines. I’ve worked on projects ranging from scientific data and spatial analysis to the development of production ELT workflows, automation tools, and client-facing analytics in industry. I enjoy working at the intersection of science, data, and real-world impact. I’m always excited to connect with people working in AI, data science, and research.

Affiliations & Experience

Oct 2025 – Present

Data Scientist

Cognano Inc., Toronto

Leading development and evaluation workflows for large-scale AI/ML systems and contributing to research initiatives including an ICLR 2026 workshop submission.

Apr 2024 – Oct 2025

Technical Data Consultant

Validere Inc., Toronto

Built production data pipelines, monitoring systems, automation tools, and ML solutions for Oil & Gas clients.

Oct 2023 – Mar 2024

Research Scientist

University of Toronto

Developed AI/ML pipelines supporting clean-energy research using PyTorch and Scikit-Learn.

Sep 2021 – Aug 2023

Research Assistant

University of British Columbia

Conducted large-scale image analysis, HPC processing, and science-policy research projects.

2021 – 2023

M.Sc. Physics

University of British Columbia

2017 – 2021

B.Sc. Physics (Honours)

Taras Shevchenko National University of Kyiv

Skills

Programming

  • Python (numpy, pandas, scipy, astropy, geopandas, shapely, rasterio, etc.)
  • Version Control (GitHub)
  • Large-scale data processing and ingestion, ETL/ELT pipelines
  • C++, R

Visualization & Monitoring

  • matplotlib, seaborn, plotly, etc.
  • AWS QuickSight
  • Datadog, Grafana

Machine Learning & LLM

  • PyTorch, Scikit-learn, TensorFlow
  • Regression, clustering, deep learning, feature engineering, model evaluation
  • LLM API, RAG

Data & Infrastructure

  • SQL
  • AWS (S3, SPICE)
  • HPC (GPU, CPU)
  • Metabase
  • Docker
  • Streamlit

Contact me