Rocket
Mini tools
Data Scientist II, Growth
Tinder
On-site
Los Angeles, CA, United States
Full-time
$145,000 -
$155,000
About Tinder
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”™
About the Role
The Growth Data Science team is looking for curious individuals excited to drive data-informed
decision-making at Tinder. We are a strategic partner to the Product team, and will be using our
comprehensive datasets to develop experiments, understand metrics, develop automated
reports, and generate exploratory insights to guide our business solutions. These insights are
key in both the performance of our business and the experience of our members.
This role has the opportunity to work on either the User Growth or Growth Platform teams within
the Data Science Team. The User Growth team focuses on validating greenspace hypotheses
and optimizing the core experience through growth levers and personalization, while the Growth
Platform team focuses on optimizing and scaling messaging strategy through strategic channels and personalization. We will work closely with you to define what team would be the best match.
decision-making at Tinder. We are a strategic partner to the Product team, and will be using our
comprehensive datasets to develop experiments, understand metrics, develop automated
reports, and generate exploratory insights to guide our business solutions. These insights are
key in both the performance of our business and the experience of our members.
This role has the opportunity to work on either the User Growth or Growth Platform teams within
the Data Science Team. The User Growth team focuses on validating greenspace hypotheses
and optimizing the core experience through growth levers and personalization, while the Growth
Platform team focuses on optimizing and scaling messaging strategy through strategic channels and personalization. We will work closely with you to define what team would be the best match.
Qualifications
Bachelor’s degree in a quantitative field, Master’s degree, or PhD with a social science background preferred.
2-4 years of professional working experience in Data Science and/or analytics.
Familiarity with two sided consumer ecosystem, specifically in the context of consumer technology.
Experience with SQL, data visualization tools (e.g., Tableau or Mode).
Hands on experience in designing and implementing experiments (e.g. randomized testing, A/B testing) to drive key product decisions is required.
Familiarity with Python/R, using descriptive and inferential statistics and machine learning models.
Demonstrated ability to collaborate effectively with design, product, and engineering teams to advance key business initiatives from conceptualization to final product delivery.
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.
2-4 years of professional working experience in Data Science and/or analytics.
Familiarity with two sided consumer ecosystem, specifically in the context of consumer technology.
Experience with SQL, data visualization tools (e.g., Tableau or Mode).
Hands on experience in designing and implementing experiments (e.g. randomized testing, A/B testing) to drive key product decisions is required.
Familiarity with Python/R, using descriptive and inferential statistics and machine learning models.
Demonstrated ability to collaborate effectively with design, product, and engineering teams to advance key business initiatives from conceptualization to final product delivery.
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.
Responsibilities
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.
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.
Benefits
Drive rigorous testing to validate hypotheses and guide business decisions.
Find the “story” in the data and share insights with Product, Engineering, and Design teams, as well as at the company level.
Serve as a data authority with a clear point of view, using data to challenge and reshape our understanding of customer behavior and business performance.
Derive and communicate data-driven recommendations on both prioritizing potential product/marketing initiatives and evaluating current initiative performance.
Define and operationalize tracking for company-wide, team-specific, and product-specific performance metrics through rollout tables, dashboards, and automated reporting.
Find the “story” in the data and share insights with Product, Engineering, and Design teams, as well as at the company level.
Serve as a data authority with a clear point of view, using data to challenge and reshape our understanding of customer behavior and business performance.
Derive and communicate data-driven recommendations on both prioritizing potential product/marketing initiatives and evaluating current initiative performance.
Define and operationalize tracking for company-wide, team-specific, and product-specific performance metrics through rollout tables, dashboards, and automated reporting.
