Ksenia Bataeva

Machine Learning Engineer

• Integrated a reinforcement learning recommendation algorithm into an email marketing campaign, resulting in conclusively positive engagement metrics during A/B testing.
• Developed a benchmarking tool for recommendation models that received positive feedback from several departments, improving cross-functional collaboration and model evaluation standards.
• Streamlined existing CI/CD workflows for the codebase, improving deployment processes and ensuring more efficient integration of new features into production environments.

Skills: Reinforcement Learning, CI/CD Workflows, Recommendation Systems, Python, Java, Data Processing

Senior Data Engineer

• Supported Central Data Science team with packaging ML models and creating MLOps with CI/CD tools like GitHub and GitLab.
• Developed and deployed analytical code-based dashboards to Google Cloud using Streamlit and Dash.
• Migrated existed AWS SageMaker ML pipelines to Vertex Al.
• Refactored and migrated around 500 Analytical Engineering pipelines to Vertex Al on time.
• Mentored Data and Machine Learning Engineers in the GCP incubator program.

Senior Machine Learning Engineer

• Defined and built ETL processes in Hive, Spark, Python, Airflow, and ClickHouse for analyzing marketing campaign performance and tracking key metrics based on data from AppsFlyer.
• Integrated MLOps tools for efficient ML model deployment and management.
• Speed up an LTV calculator tool from almost 1 minute to seconds with advanced pre-aggregations.
• Built a predictive CLV model. Improved predicted cohort revenue on 180 days based on first 7 days after acquisition with using this model up to 12% in terms of MAPE.

Senior Machine Learning Engineer

• Developed a set of decoders for weather data and established robust data pipelines for machine learning services using Python, Kafka, and Docker, enhancing data availability from day to hour.
• Built scalable data-centric microservices that transformed and integrated data from multiple sources into internal services, improving overall system interoperability and data readiness for ML models and analysis.
• Created predictive models for river water levels using advanced techniques like LSTM and Gradient Boosting, achieving an accuracy rate of over 85% in forecasting critical water levels.
• Conducted comparative analyses of satellite-based indices such as NDVI and FWI to assess environmental risks effectively, contributing to improved decision-making processes in disaster management.
• Organized successful hackathons focused on Al applications in emergency management, fostering innovation and collaboration among teams while generating new ideas for practical solutions.

Technical Lead

• Designed and led the implementation of a contractor compliance monitoring solution that streamlined the selection process for reliable companies.
• Led the development of a modern Geographic Information System (GIS) that enabled real-time collection and analysis of environmental data through a user-friendly browser interface, enhancing data accessibility for stakeholders.
• Spearheaded the design and development of both front-end and back-end code for various web applications tailored to external client needs, ensuring high performance and scalability across multiple platforms.
• Mentored junior developers on coding best practices and project management methodologies, fostering a collaborative team environment.