Understand detailed usage of products by analyzing user behavior data, translating complex questions into analytical plans, and building robust product metrics.
Run and measure product experiments (A/B tests) from design through interpretation, clearly articulating results and recommendations to stakeholders.
Develop and maintain key performance indicators (KPIs) and operational metrics for product features and overall business health.
Provide actionable insights for Product Managers on user engagement, feature adoption, and growth opportunities to directly inform the product roadmap.
Build deep-dive reports for Executive Leaders on critical business trends and the performance of strategic initiatives, presenting findings in a clear, compelling narrative.
Collaborate with engineering teams on data logging, instrumentation, and ensuring the accuracy of product data pipelines.
Apply statistical modeling and machine learning techniques to solve business problems (e.g., churn prediction, segmentation, propensity modeling).
Design and implement data visualizations and self-service dashboards to democratize data access across the organization.
Partner with cross-functional teams (Product, Engineering, Marketing, Sales) to define data requirements and analytical objectives.
Coach and mentor junior analysts and data scientists on best practices for data visualization, statistical analysis, and clear communication of results.

5–6+ years of experience in a Data Scientist or Product Analyst role, preferably within a technology or SaaS company.
Expert proficiency in SQL for complex data extraction and manipulation.
Strong proficiency in a statistical programming language (Python or R), including libraries for data manipulation, analysis, and statistical modeling.
Proven experience designing, launching, and analyzing A/B tests or other product experiments.
Experience with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery) and data visualization tools (e.g., Sigma, Tableau, Looker).
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Advanced knowledge of statistical methods (regression, hypothesis testing, time series analysis) and their application to business problems.
Excellent verbal and written communication skills, with the ability to present complex analytical findings to both technical and executive audiences.
Demonstrated ability to work independently and drive projects from conception to completion with minimal supervision.
Proven experience influencing senior stakeholders and driving alignment on data-informed decisions.

Senior Data Scientist, Data Insights

Key skills