Senior Data Scientist, Recommendations
Match Group
full-time
Posted on:
Location Type: Hybrid
Location: Los Angeles • California • 🇺🇸 United States
Visit company websiteSalary
💰 $160,000 - $170,000 per year
Job Level
Senior
Tech Stack
PythonSQL
About the role
- Work closely with Product, Engineering, and ML to identify and evaluate new opportunities; frame hypotheses, define success metrics and guardrails, and translate findings into clear product recommendations.
- Support the ML team in improving algorithms across retrieval, ranking, and personalization; strengthen offline/online evaluation and alignment.
- Define and lead experimentation design and analysis tailored to a two‑sided marketplace; drive meta-analyses and playbooks that uplevel reads and decision quality.
- Build tools and dashboards to improve experiment reads and KPI monitoring; standardize templates and health checks for fast, reliable iteration.
- Deliver executive-ready presentations and docs that clarify options, tradeoffs, risks, and expected business impact.
- Be a trusted and respected partner for the Recs pod, focused on delivering the best recommendations for our worldwide member base.
- Mentor and inspire other data scientists; review analyses and elevate experimentation, causal inference, and model evaluation practices across the team.
Requirements
- Bachelor’s, Master’s, and/or Ph.D. degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics, or related fields).
- 5+ years of professional experience in data science/analytics, with meaningful time in recommender systems, ranking, search, or personalization at consumer scale (or equivalent impact/complexity).
- Fluency in SQL and Python (required).
- Deep understanding of statistics and causal inference; hands-on experience designing and analyzing online experiments (A/B, variance reduction, sequential testing) and applying quasi-experimental methods when appropriate.
- Strong product sense and analytical rigor; ability to frame the right questions, choose fit-for-purpose methods, and land actionable recommendations with cross-functional partners.
- Familiarity with machine learning for recommendations, including offline/online metric design and model evaluation for ranking/personalization use cases.
Benefits
- Unlimited PTO (with no waiting period), 10 annual Wellness Days
- Time off to volunteer and charitable donations matching
- Comprehensive health, vision, and dental coverage
- 100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP)
- 100% paid parental leave (including for non-birthing parents), family forming benefits, and Milk Stork, which provides access to breast milk shipping for business travel, surrogacy, and employee relocation
- Investment in your development: mentorship through our MentorMatch program, access to 6,000+ online courses through Udemy, and an annual stipend for your professional development
- Investment in your wellness: access to mental health support via Modern Health, and Insight Timer; paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy
- Free premium subscriptions for several Match Group apps – including Tinder Platinum!
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
SQLPythonstatisticscausal inferenceA/B testingvariance reductionsequential testingmachine learningrecommender systemsdata analysis
Soft skills
analytical rigorproduct sensementoringcommunicationcollaborationpresentation skillsproblem framingdecision qualitytrustworthinessinspiration