Data Scientist

About the role

The role owns the entire data science lifecycle, turning complex datasets into scalable predictive models and actionable insights that drive product strategy and user growth. The team works closely with engineering and product leaders to solve ambiguous problems using advanced statistical modeling, machine learning, and deep exploratory data analysis.

Responsibilities

• Develop, validate, and deploy statistical and machine learning models in Python using scikit-learn, XGBoost, and PyTorch
• Design and execute rigorous A/B tests to measure feature impact, analyzing experimental results to guide product roadmap decisions
• Build robust data pipelines in SQL and PySpark to aggregate telemetry, user behavior, and operational metrics
• Collaborate with data engineers to optimize feature stores and ensure data integrity across training and serving layers
• Communicate complex modeling results and strategic recommendations to both technical and executive stakeholders

Requirements

• 3–6 years of experience in data science, quantitative analytics, or applied machine learning in a production environment
• Advanced proficiency in Python, SQL, and statistical data analysis libraries (Pandas, NumPy, SciPy)
• Demonstrated experience designing, running, and interpreting complex A/B tests and causal inference models
• Solid understanding of software engineering best practices, version control, and CI/CD pipelines

Qualifications

• Bonus: MS or PhD in a quantitative field such as Statistics, Computer Science, Economics, or Mathematics