Yerkebulan Askarbekov

Lead Data Scientist/MLOps Engineer — Technical Lead & Architect

MDigital

Leads data platform architecture and MLOps practices for an ML/AI team, building production infrastructure and pipelines across tens of data sources.

• Architected and maintained data infrastructure supporting AI/ML systems • Designed ETL pipelines and data quality frameworks for production ML workflows, scaling up to tens various data sources • Built and maintained MLOps practices of the ML/AI team • Mentored teams of developers and researchers

Data Scientist / ML & AI Engineer

MDigital

Built voice analytics, LLM integrations, BI reporting, and time-series models for sales planning, while mentoring machine learning interns.

• Developed an analytical system for voice processing • Integrated LLMs into the business processes of the company • Built and maintained BI analytics platforms using Apache Superset and Airflow for automated reporting • Integrated predictive models to automate sales planning processes leveraging time series analysis (Python, scikit-learn, PyTorch) • Mentored interns on machine learning fundamentals, including supervised learning and scikit-learn

Data Analyst / Data Engineer

Asia Retail

Optimised SQL Server workloads, cutting ETL and dashboard query times by about 50%, and built 20+ Airflow DAGs for enterprise analytics.

• Optimised OLAP/OLTP systems (SQL Server) for enterprise reporting; tuned complex queries on 10M+ row tables, cutting execution time by ~50% for ETLs and dashboards • Built and maintained 20+ Airflow DAGs running at frequencies from 15 minutes to monthly, orchestrating ETL loads, report refreshes, data quality checks, and retroactive backfills • Designed dimensional models using star and snowflake schemas; applied Kimball and Inmon methodologies for data warehouse (DWH) design • Performed data quality validation and SLA enforcement for analytics pipelines

Data Science / Data Engineer Intern

Development Monitors LLC

Built climate data pipelines and integrated model results into dashboards supporting risk analysis for World Bank projects.

• Built data pipelines to ingest and update climate datasets feeding downstream risk analysis for World Bank projects • Integrated model outputs into climate risk dashboards; presented findings to cross-functional teams including data scientists and policy experts

Data Science/Engineering Intern

Scientific Research Station of RAS

Migrated research processing from MATLAB to Python and built a data collection application, reducing report generation from hours to seconds.

• Migrated MATLAB ecosystems to Python, automating data processing • Created a desktop application for data collection, cleansing, and visualisation using Python and its libraries • Reduced report generation time from several hours to 5–10 seconds

B.Sc., Applied Mathematics

American University of Central Asia (AUCA)