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Data Scientist II (Product Analytics, Recommendations )

California, United States (Hybrid)

Data Scientist II (Product Analytics, Recommendations )

19 Hours ago • 2-4 Years

About the job

Summary_{By Outscal}

Data Scientist II with 2-4 years experience in product analytics, recommendations. Must have SQL, data visualization, A/B testing, and Python/R. Experience with machine learning models is a plus.

Our Mission

Launched in 2012, Tinder® revolutionized how people meet, growing from 1 match to one billion matches in just two years. This rapid growth demonstrates its ability to fulfill a fundamental human need: real connection. Today, the app has been downloaded over 630 million times, leading to over 97 billion matches, serving approximately 50 million users per month in 190 countries and 45+ languages - a scale unmatched by any other app in the category. In 2024, Tinder won four Effie Awards for its first-ever global brand campaign, “It Starts with a Swipe”™"

Our Values

One Team, One Dream

We work hand-in-hand, building Tinder for our members. We succeed together when we work collaboratively across functions, teams, and time zones, and think outside the box to achieve our company vision and mission.

Own It

We take accountability and strive to make a positive impact in all aspects of our business, through ownership, innovation, and a commitment to excellence.

Never Stop Learning

We cultivate a culture where it’s safe to take risks. We seek out input, share honest feedback, celebrate our wins, and learn from our mistakes in order to continue improving.

Spark Solutions

We’re problem solvers, focusing on how to best move forward when faced with obstacles. We don’t dwell on the past or on the issues at hand, but instead look at how to stay agile and overcome hurdles to achieve our goals.

Embrace Our Differences

We are intentional about building a workplace that reflects the rich diversity of our members. By leveraging different perspectives and other ways of thinking, we build better experiences for our members and our team.

Data Science - Product Analytics, Recommendations

The Core Data Science team seeks a passionate Data Scientist with a talent for transforming complex problems into actionable hypotheses that can be addressed through rigorous data analysis and A/B testing. In this role, you’ll collaborate closely with the Recommendations team to refine Tinder’s recommendation algorithms and lead initiatives that enhance member engagement and drive revenue growth. We’re looking for innovative, resourceful problem solvers who are deeply invested in our product and excited by the opportunity to work with extensive, sophisticated datasets. As a Data Scientist focused on Analytics, you will work cross-functionally with Product, Marketing, Engineering, and Finance teams to elevate our platform. You will leverage comprehensive user behavior data to design experiments, build forecasting models, create automated reports, and deliver impactful insights to inform strategic business decisions.

Where you’ll work: This position is in San Francisco, CA, Palo Alto, CA, or Los Angeles.

What You'll Do:

Drive rigorous testing to validate hypotheses and guide business decisions.
Find the “story” in the data and readily share insights with product, engineering, and design as well as at a company level.
Be an authority with a point of view for the organization, using data to constantly challenge and reshape our current understanding of customer behavior and business performance.
Derive and communicate data-driven recommendations regarding both the prioritization of potential product/marketing initiatives and the performance of current initiatives.
Define and operationalize the detailed tracking of company-wide, team-specific, and product-specific performance metrics via rollout tables, dashboards, and automated reporting.

What you’ll need:

Bachelor’s degree in a quantitative field (e.g. Economics, Computer Science, Statistics), Master’s degree or PhD preferred 2-4 years of professional working experience in Data Science and/or analytics.
Experience with SQL, data visualization tools (e.g., Tableau or Mode), and A/B testing is required.
Familiarity with Python/R, using descriptive and inferential statistics and machine learning models.
Ability to develop a nuanced business understanding, testable hypotheses, and significant findings from data.
Ability to present data, actionable insights, technical concepts, and approaches to technical and non-technical audiences.

Differentiators

Ability to develop a nuanced business understanding, testable hypotheses, and meaningful findings from dataEagerness to identify and explore new product/marketing opportunities, potential improvements to our data infrastructure, and unanswered questions about customer behavior
Curious about how things work, from both a business and technical perspective, could result in identifying and exploring new product opportunities, potential improvements to our data infrastructure, and deepening our understanding of member behavior.
Proactive collaborator skilled in engaging with cross-functional teams (Product, Engineering, Machine Learning) to influence decision-making, confidently voicing concerns and alternative perspectives
Ability to prioritize time across multiple projects and communicate timelines

Commitment to Inclusion

At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here: https://www.lifeattinder.com/dei

If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please speak to your Talent Acquisition Partner directly.