Lead the design, development, and deployment of advanced ML models and predictive algorithms to solve critical business problems, such as churn prediction, user segmentation, and product usage forecasting.
Serve as a technical subject matter expert, guiding the team on best practices in statistical analysis, experimentation design, and code quality.
Partner with PMs and Engineers to translate ambiguous business questions into rigorous data science projects with actionable outcomes.
Drive the adoption of MLOps best practices, ensuring models are scalable, reproducible, and monitored effectively in production.
Perform deep-dive analyses on user behavior and product performance to identify opportunities for optimization and growth.
Mentor and coach other data scientists and analysts, fostering a culture of continuous technical learning and innovation.
Communicate complex technical findings to non-technical stakeholders through compelling data storytelling and visualization.
Requirements
7+ years of experience in DS, Statistics, or a related field, with a proven track record of delivering high-impact machine learning solutions.
Expert-level proficiency in Python for data manipulation, statistical analysis, and model development (pandas, scikit-learn, numpy, etc.).
Advanced knowledge of SQL for complex data querying and performance optimization.
Strong hands-on experience with a breadth of modeling techniques, including:
Supervised learning (Regression, Random Forests, Gradient Boosting like XGBoost/LightGBM)