The Match Group Core Data team is seeking a Senior Data Analyst to help identify and unlock product and cross-brand business opportunities at the enterprise scale across Match Group, which includes brands such as Tinder, Hinge, and Plenty of Fish. Reporting to the Senior Director of Analytics Strategy & Innovation, this person will serve as a trusted partner to Brand Senior Leadership, Product, Data Engineering, and corporate teams.
This role is ideal for someone who can move fluidly between hands-on analysis, product strategy, experimentation, and data foundation work. You will help define how we measure our enterprise business, uncover portfolio-wide opportunities, and turn complex customer, brand, and operational signals into actionable insights that improve outcomes across Match Group’s consumer dating ecosystem.
How you’ll make an impact:
Define and evolve KPIs, including platform health, adoption, quality, and business impact across brands.
Partner with Product Managers and Product Leadership to frame problems, size opportunities, define success metrics, and inform roadmap priorities.
Lead product feature experiment design, feature performance measurement, cohort analysis, and post-launch evaluation.
Analyze large, complex datasets to size the reach and impact of product feature opportunities, leveraging cross-brand datasets.
Partner with Data Engineering to improve instrumentation, metric definitions, data models, and self-service analytics.
Build dashboards and analytical frameworks that help teams monitor performance and make faster decisions.
Translate ambiguous questions into clear analysis, practical recommendations, and compelling narratives.
We could be a match if:
7+ years of experience using quantitative analysis to drive product and business decisions in digital product environments.
4+ years of experience directly supporting Product Managers or embedded within a product organization.
Highly capable storyteller who can turn a hypothesis into a validated, compelling opportunity for our internal customers and senior executives.
Experience owning product metrics and evaluating feature performance through experimentation, funnel analysis, retention analysis, and segmentation.
Strong technical analytics skills across large datasets, from event-level data to executive reporting.
Strong understanding of product analytics in multi-sided or B2B2C ecosystems.
Experience improving instrumentation, event schemas, and data models to increase data quality and speed to insight.
Familiarity with split testing and experimentation methods, including statistical significance testing.
Advanced SQL skills
Experience with BI and visualization tools such as Databricks Dashboards, Looker, Tableau, Quicksight, or similar.
Very strong communication skills and the ability to influence both technical and non-technical stakeholders.
Familiarity with user growth analytics preferred.
