Data Scientist

About The Role

The role focuses on translating complex business problems into structured analytical frameworks, designing rigorous statistical experiments, and building predictive models that drive strategic product and operational decisions.

The position sits within a highly collaborative team of data scientists and machine learning engineers, taking ownership of the end-to-end analytical lifecycle from exploratory data analysis to productionizing model outputs and designing automated dashboard suites.

Key Responsibilities

• Develop, evaluate, and deploy predictive models and statistical algorithms using Python and SQL to optimize user experience and operational workflows
• Design and execute rigorous A/B testing frameworks, including power analysis, sample size determination, and post-hoc segmentation to measure the impact of product features
• Build and maintain robust ETL pipelines in Snowflake or dbt, transforming raw telemetry data into clean, structured schemas optimized for analytical modeling
• Collaborate with product and engineering teams to define key performance indicators, design telemetry schemas, and establish automated monitoring pipelines for model performance
• Translate complex analytical findings into actionable business recommendations and communicate them effectively to cross-functional stakeholders through clear visualizations and structured reports

What We Are Looking For

• 3-6 years of experience as a Data Scientist or quantitative analyst, with a proven track record of delivering end-to-end analytical solutions in a fast-paced environment
• Advanced proficiency in Python and SQL, with hands-on experience using data science libraries such as pandas, NumPy, scikit-learn, and Statsmodels
• Deep theoretical and practical knowledge of statistics, including hypothesis testing, regression analysis, experimental design, and causal inference
• Experience with cloud data warehouses (such as Snowflake, BigQuery, or Redshift) and business intelligence tools (such as Tableau, Looker, or PowerBI)
• Bachelor's or Master's degree in a quantitative field such as Statistics, Computer Science, Economics, Mathematics, or a related discipline
• Bonus: Experience with dbt, familiarity with PySpark or Databricks, or exposure to MLOps tools like MLflow