Senior Data Scientist, Data Insights

Decision Foundry•Seattle, WA

6h•Remote

About The Position

We are seeking a Senior Data Scientist to join the Data Insights team for our client who will be a key individual contributor, applying statistical rigor and advanced analytical techniques to extract value from the product and business data. This role requires a strong understanding of product usage to provide actionable insights that drive business strategy and feature development. This is a senior, hands-on analytical role focused on end-to-end ownership, independent execution, deep-dive analysis, and translating complex data into clear business recommendations. You'll work closely with Product Managers, Executive Leaders, and Engineering teams to define key metrics, measure product health, and inform data-driven decisions. Success in this role requires a strong foundation in statistics, advanced SQL skills, and proven experience in product experimentation and reporting for a technical audience.

Requirements

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.
Demonstrated ability to translate open-ended business questions into structured analytical projects and deliverables.
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.

Nice To Haves

Experience analyzing data related to developer tools or B2B SaaS products.
Advanced degree (M.S. or Ph.D.) in a quantitative field such as Statistics, Computer Science, Economics, or Mathematics.
Knowledge of container technologies.

Responsibilities

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.
Influence product and business strategy by framing data-informed tradeoffs and recommendations for senior leaders.
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.
Ensure data quality and integrity for all analytical outputs and reports.
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.