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:
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Define and evolve KPIs, including platform health, adoption, quality, and business impact across brands.
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Partner with Product Managers and Product Leadership to frame problems, size opportunities, define success metrics, and inform roadmap priorities.
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Lead product feature experiment design, feature performance measurement, cohort analysis, and post-launch evaluation.
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Analyze large, complex datasets to size the reach and impact of product feature opportunities, leveraging cross-brand datasets.
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Partner with Data Engineering to improve instrumentation, metric definitions, data models, and self-service analytics.
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Build dashboards and analytical frameworks that help teams monitor performance and make faster decisions.
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Translate ambiguous questions into clear analysis, practical recommendations, and compelling narratives.
We could be a match if:
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7+ years of experience using quantitative analysis to drive product and business decisions in digital product environments.
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4+ years of experience directly supporting Product Managers or embedded within a product organization.
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Highly capable storyteller who can turn a hypothesis into a validated, compelling opportunity for our internal customers and senior executives.
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Experience owning product metrics and evaluating feature performance through experimentation, funnel analysis, retention analysis, and segmentation.
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Strong technical analytics skills across large datasets, from event-level data to executive reporting.
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Strong understanding of product analytics in multi-sided or B2B2C ecosystems.
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Experience improving instrumentation, event schemas, and data models to increase data quality and speed to insight.
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Familiarity with split testing and experimentation methods, including statistical significance testing.
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Advanced SQL skills
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Experience with BI and visualization tools such as Databricks Dashboards, Looker, Tableau, Quicksight, or similar.
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Very strong communication skills and the ability to influence both technical and non-technical stakeholders.
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Familiarity with user growth analytics preferred.