Data Scientist, Product Analytics

🇺🇸 Hybrid - San Francisco, CA

🕑 Full-Time

💰 $150K - $200K

💻 Data Science

🗓️ May 21st, 2025

DBT Jupyter Looker

Edtech.com's Summary

Handshake is hiring a Data Scientist, Product Analytics. The role involves partnering with cross-functional teams to deliver actionable insights and develop experimentation frameworks for product and growth decisions. Responsibilities include identifying key metrics, analyzing user behavior, and contributing to experiment design and analysis to support feature development.

Highlights

Collaborate with product managers and engineers to drive analytics workstreams.
Analyze user behavior to identify trends and improvement opportunities.
Proficiency in SQL and experience with Python or R in Jupyter-style notebooks.
Experience with A/B testing and data-driven product development.
Compensation range: $150,000-$200,000.
Over 3 years of professional data science experience required.
Experience with BI tools like Looker, Hex, or Mode.

Data Scientist, Product Analytics Full Description

Everyone is welcome at Handshake. We know diverse teams build better products and we are committed to creating an inclusive culture built on a foundation of respect for all individuals. We strongly encourage candidates from non-traditional backgrounds, historically marginalized or underrepresented groups to apply.

Your impact

Handshake is looking for a Data Scientist, Product Analytics to help shape how we measure and grow the impact of our products across students, employers, and university partners. In this role, you’ll partner with product, engineering, and analytics stakeholders to deliver actionable insights and experimentation frameworks that guide key product and growth decisions. You’ll be embedded in our Data team and report to the Senior Manager of Data & Analytics.

Your role

As a Data Scientist at Handshake, you will:
- Collaborate with product managers and engineers to identify key metrics and drive analytics workstreams
- Analyze user behavior to uncover trends, patterns, and opportunities for product improvement
- Contribute to experiment design, implementation, and analysis to guide feature development
- Build and maintain dashboards and reports to support ongoing tracking and decision-making
- Help define and refine data models in partnership with Analytics Engineering
- Translate complex data findings into clear, actionable insights for cross-functional stakeholders

Your experience

3+ years of professional data science experience
Experience using data to support product development, including working with cross-functional teams
Proficiency in SQL and comfort working in Jupyter-style notebooks using Python or R
Awareness with A/B testing and experimentation best practices
Ability to conduct analysis across user cohorts, funnels, and time-series datasets
Robust written and verbal communication skills, especially in summarizing insights for non-technical audiences
Experience with BI tools such as Looker, Hex, or Mode

Bonus areas of expertise

Exposure to product analytics in a multi-sided marketplace
Knowledge with dbt or similar data modeling frameworks
Prior experience contributing to data-informed product strategies

Compensation range

$150,000-$200,000

Original Job Description

Your impact

Your role

As a Data Scientist at Handshake, you will:
- Collaborate with product managers and engineers to identify key metrics and drive analytics workstreams
- Analyze user behavior to uncover trends, patterns, and opportunities for product improvement
- Contribute to experiment design, implementation, and analysis to guide feature development
- Build and maintain dashboards and reports to support ongoing tracking and decision-making
- Help define and refine data models in partnership with Analytics Engineering
- Translate complex data findings into clear, actionable insights for cross-functional stakeholders

Your experience

3+ years of professional data science experience
Experience using data to support product development, including working with cross-functional teams
Proficiency in SQL and comfort working in Jupyter-style notebooks using Python or R
Awareness with A/B testing and experimentation best practices
Ability to conduct analysis across user cohorts, funnels, and time-series datasets
Robust written and verbal communication skills, especially in summarizing insights for non-technical audiences
Experience with BI tools such as Looker, Hex, or Mode