Data Scientist

About The Role

The role owns the end-to-end data science lifecycle, turning complex datasets into predictive models and actionable business intelligence that drive product strategy.

You will collaborate closely with product managers and data engineers to build robust pipelines, design experiments, and deliver insights where precision and scalability are paramount.

Key Responsibilities

• Design, train, and validate statistical and machine learning models to solve complex forecasting and classification problems
• Build automated ETL pipelines in Python and SQL to ingest, clean, and process large-scale structured and unstructured datasets
• Design and analyze A/B tests to measure product feature impact, ensuring statistical significance and actionable takeaways
• Deploy models into production environments and monitor performance metrics to prevent drift and degradation over time
• Communicate complex technical findings clearly to cross-functional stakeholders through compelling data visualizations and reports
  
  

What We Are Looking For

• 3–6 years of experience in data science, applied statistics, or quantitative analytics in a production environment
• Advanced proficiency in Python and SQL, with strong working knowledge of pandas, scikit-learn, and data visualization libraries
• Demonstrated expertise in hypothesis testing, experimental design, and statistical modeling techniques
• Familiarity with cloud data platforms like Snowflake, BigQuery, or AWS Redshift and orchestration tools like Airflow
• Bonus: Experience deploying models via Docker/Kubernetes, familiarity with LLM architectures, or a Master's degree in a quantitative field