Data Scientist
Current• Develops end-to-end machine learning pipelines to create Lifetime Value (LTV) prediction models which forecasts LTV with 85 - 90% accuracy for thousands of performance marketing ad campaigns.• Created fraud detection model to analyze the performance of user acquisition campaigns to identify and automatically block underperforming or fraudulent installs. This process saves between $30,000 - $50,000 (USD) per month.• Writes advanced SQL queries (Postgres & Athena) which are leveraged… Show more • Develops end-to-end machine learning pipelines to create Lifetime Value (LTV) prediction models which forecasts LTV with 85 - 90% accuracy for thousands of performance marketing ad campaigns.• Created fraud detection model to analyze the performance of user acquisition campaigns to identify and automatically block underperforming or fraudulent installs. This process saves between $30,000 - $50,000 (USD) per month.• Writes advanced SQL queries (Postgres & Athena) which are leveraged for in-depth product data analysis, providing valuable insights for informed decision-making.• Schedules and leads regular meetings with various stakeholders to share results and analysis, and obtain feedback on platform performance, and brainstorm new features to be implemented.• Built and maintains a dashboard web application (Streamlit framework) for the performance marketing team which enables its users to conduct cohort analysis, understand prediction data and visualize accuracy metrics and various KPIs.• Utilizes data engineering skills to develop and implement high-performance data pipelines to automate ETL processes. Show less