Data Scientist

About The Role

The role focuses on translating complex business challenges into robust predictive models and analytical frameworks. The team builds and refines the core algorithms that drive decision-making, personalization, and operational efficiency across the entire product ecosystem.

This position requires a practitioner who balances theoretical statistical knowledge with strong engineering execution. The role collaborates closely with product managers and data engineers to design experiments, validate hypotheses, and ship production-grade data products.

Key Responsibilities

• Design, build, and deploy predictive models and statistical algorithms to optimize user experience, retention, and conversion metrics
• Develop and maintain robust data pipelines in SQL and Python to extract, clean, and prepare features for model training
• Define experimental frameworks and conduct rigorous A/B testing, including sample size estimation, power analysis, and post-hoc segmentation
• Perform exploratory data analysis to identify new growth opportunities, product frictions, and behavioral patterns within large-scale datasets
• Collaborate with engineering teams to integrate offline models into real-time production serving systems and monitor their post-deployment performance
• Communicate complex technical findings, model methodologies, and experimentation results to stakeholders through clear documentation and dashboards

What We Are Looking For

• 3–6 years of professional experience as a Data Scientist or in a quantitative analytical role, preferably within a high-growth tech environment
• Advanced proficiency in Python (including pandas, numpy, scikit-learn) and complex SQL queries for data extraction and manipulation
• Deep theoretical and practical understanding of statistics, experimental design, regression analysis, and machine learning classification/clustering techniques
• Experience working with cloud data warehouses (e.g., Snowflake, BigQuery) and business intelligence tools (e.g., Tableau, Looker) for reporting
• MS or PhD in a highly quantitative field (Computer Science, Statistics, Mathematics, Economics, or Physics)
• Bonus: Experience with PySpark or distributed computing frameworks, and familiarity with containerization tools like Docker and Kubernetes