Data Scientist Los Angeles, California Department Product Analytics

Position: Data Scientist Hot Job Los Angeles, California Department Product Analytics

The Role:

Take the Lead

We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down.

Move Fast

We have a bias for action and urgency. Something that could be done tomorrow would be better if done today.

Better Together

We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate.

Real Talk

We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same.

Safety First

We act with integrity, transparency, and consistency so people feel safe—whether they’re swiping, matching, or working alongside us.

Spark Fun

We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters.

The Analytics team is looking for curious individuals excited to drive data-informed decision-making are a strategic partner to Product, Design, Engineering, and Machine Learning, using our comprehensive datasets to develop experiments, understand and evolve metrics, build automated reporting, and generate exploratory insights that guide business and product decisions. These insights are key to both the performance of our business and the experience of our members

.

We are hiring Data Scientists into a shared pipeline with opportunities to join one of several product pods, including Core

, Recommendations

, and Growth

.

Core

focuses on the end-to-end member experience across registration, swiping, matching, and messaging, ensuring a healthy, engaging marketplace.

Recommendations

focuses on ranking, personalization, and signals to surface the right profiles and experiences at the right time.

Growth

focuses on validating new green space hypotheses, acquisition, activation, and lifecycle experiences (including messaging and channels) that help members discover more value on Tinder.

During the interview process, we’ll work closely with you to determine which pod is the best match based on your background, interests, and our current needs.

Where you’ll work:

This position can be located in Los Angeles, San Francisco, Palo Alto, CA, or Dallas, TX

In this role, you will:

• Drive rigorous testing (e.g., A/B and quasi-experiments) to validate hypotheses and guide product and business decisions across Core, Recommendations, and Growth.
• Find the “story” in the data and share insights with product, engineering, design, and machine learning partners, as well as at a company level.
• Be an authority with a point of view for the organization, using data to continually challenge and reshape our understanding of member behavior and business performance.
• Derive and communicate data‑driven recommendations on both the prioritization of potential initiatives and the performance of current features and experiments.
• Define and operationalize metrics at the company, team, and product level via rollout tables, dashboards, and automated reporting.

You’ll need:

• Bachelor’s degree in a quantitative field (or equivalent experience);

Master’s degree or PhD with a social science background preferred.

• 2–4 years of professional experience in Data Science and/or Analytics

.

• Familiarity with two‑sided consumer ecosystems

, ideally within consumer technology or marketplaces

.

• Experience with SQL and data visualization tools (e.g., Tableau or Mode).
• Hands‑on experience designing and implementing experiments (e.g., randomized tests, A/B tests) to drive key product decisions.
• Familiarity with Python or R, using descriptive and inferential statistics and machine learning models

.

• Demonstrated ability to collaborate effectively with design, product, engineering, and/or machine learning teams to move initiatives from concept to launch.
• Ability to develop a nuanced business understanding

, frame testable hypotheses

, and extract meaningful findings from data.

• Ability to present data, insights, and technical concepts to both technical and non-technical audiences.

Differentiators:

• Deep curiosity about how things work—from both a business and technical perspective that leads you to identify and explore new product opportunities, improve data…