Senior Product Analytics Lead — Hybrid (SF)

Strava; United States; Hybride; USD 110 000 - 150 000; Plein temps

Résumé du poste

Strava in San Francisco is seeking an experienced data analytics professional to join a cross-functional product team. You will collaborate with product managers, engineers and researchers to accelerate learning, drive data-informed decisions and define data-inspired solutions for athletes.

The role emphasizes end-to-end data work—from instrumentation and ETL to dashboards—plus ownership of key metrics and experimentation practices. A strong background in SQL, Python/R and BI tools is required.

Qualifications

• 4+ years of analytics, data science or related quantitative field.
• Experience with consumer-facing tech is preferred.
• Strong SQL and BI tooling experience.
• Experience with experimentation and A/B testing.

Responsabilités

• Analyze data to produce insights on athlete usage and opportunities to improve experience.
• Collaborate with product managers to inform strategy within a product team.
• Advise on A/B test design and interpretation while upholding experimentation best practices.
• Evaluate data tracking quality and work with engineers to implement solutions.
• Own end-to-end data solutions including instrumentation, ETL and modeling and dashboards.
• Provide the “source of truth” for internal consumers by owning critical analytical reporting.
• Collaborate with data science and data engineering to improve technological craftsmanship.

Connaissances

SQL expertise

Python

R

A/B testing

Data visualization

ETL concepts

Communication

Formation

Bachelor's degree in a quantitative field

Outils

DBT

Python

Description du poste

Strava in San Francisco is seeking an experienced data analytics professional to join a cross-functional product team. You will collaborate with product managers, engineers and researchers to accelerate learning, drive data-informed decisions and define data-inspired solutions for athletes.

The role emphasizes end-to-end data work—from instrumentation and ETL to dashboards—plus ownership of key metrics and experimentation practices. A strong background in SQL, Python/R and BI tools is required.