Senior Data Scientist, Data Products & Metrics

TOGETHXR; San Francisco, Northern (CA, KY); On-site; USD 140,000 - 190,000; Full time

Job summary

Strava is seeking a Data Scientist to join the Data Products team, shaping measurement strategies and guiding ML evaluation. The role partners closely with ML Engineers to define success criteria and ensure high-quality, scalable data products that drive user experiences at scale.

You will lead the development of dashboards and metrics across cross-domain models, while owning experimentation, monitoring, and drift detection to protect data quality in athlete-facing features.

Qualifications

• 5+ years of experience in data science or related quantitative domain, including hands-on ownership of model evaluation and measurement for systems running in production.
• Experience defining evaluation frameworks for ambiguous ML problems, including baseline selection, offline and online metric design, and validation strategies where ground truth is imperfect.

Responsibilities

• Define what "good" looks like for Strava's internal models and the ML products built on top of it, setting evaluation frameworks, offline and online metrics, and quality bars the team steers by.
• Build the measurement layer for cross-domain ML products, scaling the org’s visibility into performance across the business
• Own experimentation and monitoring for production models and contribute to monitoring of key metrics and drift detection for enriched datasets, ensuring quality for downstream athlete-facing experiences.
• Identify and size AI/ML product opportunities, translating ambiguous problem spaces into scoped initiatives with defined success criteria.
• Serve as the data science domain expert for the team, raising the standard for baselines, validation, and evidence quality across ML engineers and cross-functional partners.

Skills

SQL proficiency

Python for data processing

Model evaluation & measurement

Cross-functional collaboration

Job description

Strava is seeking a Data Scientist to join the Data Products team, shaping measurement strategies and guiding ML evaluation. The role partners closely with ML Engineers to define success criteria and ensure high-quality, scalable data products that drive user experiences at scale.

You will lead the development of dashboards and metrics across cross-domain models, while owning experimentation, monitoring, and drift detection to protect data quality in athlete-facing features.