Public profile
@mira
Data Scientist | Applied ML Engineer
My background in applied ML, includes recommendation systems, forecasting, scoring and segmentation, with more recent work on RAG applications.
The projects I work on have covered the full ML lifecycle, from problem framing and model development to evaluation, integration, and production deployment. A product-driven approach has been a big part of that work. Before choosing a modeling approach, we tried to be explicit about the outcome we wanted, the decision the system should improve, and the metric that would tell us whether it was actually successful. In practice, that meant treating model quality as only one part of the problem, alongside reliability, usability, and how the system performed in real production workflows.
Experience, skills, projects, and achievements.
Data Scientist | Applied ML Engineer
Hero’s Journey
Oct 2025 — PresentBuilt and productionized applied ML systems across recommendation, forecasting, scoring, segmentation, and LLM/RAG use cases. Worked on the supporting ML infrastructure, including Airflow datamarts, FastAPI-based serving, AWS deployment, and production monitoring.
Philip Morris International
Aug 2024 — Oct 2025Built and maintained B2B/B2C data pipelines and Snowflake reporting workflows using Matillion, Amazon S3, SQL, and Snowflake. Improved data quality and governance through standardized metadata, KPI definitions, validation rules, and automated data ingestion.
Nazarbayev University
Aug 2023 — May 2024Developed a recommendation system for personalized content ranking using tree-based ML models and NLP embeddings. Evaluated and compared recommendation approaches using ranking and classification metrics.
Nazarbayev University
2020 — 2024