Senior Product Data Scientist - Experimentation & KPIs NEW

The Briefed; San Francisco (CA); On-site; USD 229,000 - 267,000; Full time

Benefits offered by this job

RSU equity

Comprehensive benefits

Remote work stipends

Job summary

Reddit in San Francisco seeks a Senior Data Scientist to drive product strategy with observational causal analysis and experiment meta-analysis. You will design ETL pipelines, build dashboards, and mentor junior data scientists while collaborating with leadership up to the C-suite.

You will lead A/B test design, broaden self-serve analytics, and measure KPIs across product surfaces. Proficiency in Python and SQL is essential, and you will bridge quantitative rigor with business outcomes to

Qualifications

• Master’s degree (or foreign equivalent) in a quantitative field plus 2 years of experience in data science/analytics.
• Bachelor’s degree (or foreign equivalent) in a quantitative field plus 5 years of progressively responsible post-baccalaureate experience in data science/ analytics.

Responsibilities

• Conduct observational causal analysis and experiment meta-analysis to shape multi-year product strategy.
• Design, execute, and analyze A/B tests to maximize organizational learnings across core product surfaces.
• Build and maintain ETL pipelines, data warehouse tables, dashboards, and self-serve analytics tools.
• Design, evaluate, and track team-level KPIs to support quarterly goal-setting and demonstrate product impact.
• Communicate analytical findings to Product, Engineering, and Design leadership to drive data-backed decisions.
• Mentor junior data scientists and cross-functional partners in data science methodologies and best practices.

Skills

A/B Testing

Causal Inference

Statistical Modeling

Machine Learning

ETL Development

KPI Design

Cross-Functional Collaboration

Data Visualization

Python Mastery

Education

Master’s Degree in Data Science/Statistics/ML/OR related quantitative discipline

Bachelor’s Degree in quantitative discipline + 5 years data science analytics experience

Tools

Python

SQL

Data Warehousing

ETL Tools

Job description

Reddit is a global community of communities built on shared interests, passion, and trust. Home to authentic conversations across 100,000+ active subreddits and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of human information.

As a Senior Data Scientist, you will develop action-oriented insights to drive core product strategy through observational causal analysis and experiment meta-analysis. Communicating directly with leadership up to the C-suite, you will uplevel experimentation practices across product teams, design robust ETL data pipelines, build executive dashboards, and measure team-level KPIs. You will serve as a bridge between quantitative rigor and business outcomes—guiding A/B test execution, modeling user behavior in Python and SQL, and mentoring junior data scientists.

Key Responsibilities

• Product Strategy & Causal Inference: Conduct observational causal analysis and experiment meta-analysis to generate actionable insights that shape Reddit’s multi-year product strategy.
• Experimentation Upleveling: Drive A/B test design, execution, and deep-dive post-hoc analyses to maximize organizational learnings across core product surfaces.
• Data Engineering & Self-Serve Infrastructure: Build and maintain new ETL pipelines, data warehouse tables, dashboards, and self-serve analytics tools enabling cross-functional partners to interact with data seamlessly.
• KPI Architecture & Measurement: Design, evaluate, and track team-level Key Performance Indicators (KPIs) to support quarterly goal-setting frameworks and demonstrate measurable product impact.
• Executive Stakeholder Alignment: Regularly engage with Product, Engineering, and Design leaders to communicate analytical findings, align business goals, and drive data-backed decision-making.
• Mentorship & Data Literacy: Mentor junior data scientists and cross-functional business partners in data science methodologies, statistical modeling, and analytical best practices.

Requirements

Education & Industry Experience

• Master’s Degree Option: Master’s degree (or foreign equivalent) in Data Science, Statistics, Machine Learning, Operations Research, Economics, Computer Science, Engineering (any field), or a related quantitative discipline + two (2) years of experience in data science, analytics, or a related quantitative occupation.
• OR
• Bachelor’s Degree Option: Bachelor’s degree (or foreign equivalent) in a quantitative discipline listed above + five (5) years of progressively responsible post-baccalaureate experience in data science or analytics.

Special Skill Requirements

1. A/B Testing & Experimentation Design: Advanced design, execution, and evaluation of online controlled experiments.
2. Causal Inference & Incrementality: Expertise in observational causal inference methods, matching techniques, and incrementality measurement.
3. Statistical Modeling & Machine Learning: Applied statistical modeling, predictive analytics, and data analysis algorithms.
4. ETL Development & Maintenance: Production ETL pipeline creation, data modeling, and data warehouse maintenance.
5. KPI Design & Goal Setting: Designing team-level metrics and goal-tracking frameworks.
6. Cross-Functional Collaboration: Partnering with Product, Design, and Engineering teams to execute business initiatives.
7. Data Visualization & Reporting: Building interactive dashboards, reporting modules, and executive summaries.
8. Python & SQL Mastery: Advanced hands-on coding proficiency in Python and complex SQL query optimization.
9. Predictive Modeling: Practical application of Machine Learning models to solve business problems.

Total Rewards & Benefits

• Compensation & Equity: Annual base salary range of $229,000.00 – $267,100.00 USD + Restricted Stock Unit (RSU) equity grants + potential sales/performance commission depending on final placement level.
• Healthcare & Income Replacement: Comprehensive medical, dental, vision coverage, gender-affirming care, and income protection programs.
• Financial & Family Support: 401(k) retirement plan with employer match, family planning support, and generous paid parental leave.
• Time Off & Remote Perks: Flexible vacation policy, paid volunteer time off, global lifestyle and workspace stipends, and continuous professional development allowances.