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Strava•24 days ago

Lead Data Scientist, Data Products

hybrid🇺🇸USSan Francisco, USsenior5+ yrs exp

Recruiter Fit Breakdown & Candid Summary

1

This is a senior-level individual contributor role for a data scientist with deep experience in production ML evaluation and measurement.

2

The ideal candidate bridges the gap between business strategy and technical execution, specifically focusing on defining 'good' for ML models.

3

Candidates should have strong experience in causal inference or complex metric design where ground truth is imperfect.

4

This role is not for those seeking a pure research or model-building role; it is heavily focused on measurement, monitoring, and product-driven data strategy.

Role Responsibilities

  • 1Define evaluation frameworks, offline/online metrics, and quality standards for internal ML models.
  • 2Build measurement layers for cross-domain ML products to improve organizational visibility.
  • 3Own experimentation and monitoring for production models, including drift detection.
  • 4Identify and size AI/ML product opportunities from ambiguous problem spaces.
  • 5Act as the domain expert to raise standards for validation and evidence quality across engineering teams.

Skills Matrix

Must-Have Skills

7 required
Data Science
Machine Learning(ML)
SQL
Python
Model Evaluation
Metric Design
Experimentation(A/B testing)

Nice-to-Have Skills

2 preferred
Causal Inference
Data Engineering
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