About the job
About the Team:
Grindr is a dynamic AI-driven platform that connects millions of LGBTQ+ individuals worldwide. With over 15 million monthly users and 130 billion messages sent each year, our lean team of under 200 members tackles complex technical challenges at an unprecedented scale.
As a Senior Data Scientist focusing on Ecosystem Health at Grindr, you will collaborate closely with product managers, designers, and engineers to establish meaningful metrics, design and analyze experiments, and derive insights that guide product development for Ecosystem Health initiatives. This team is dedicated to enhancing user retention by fostering a safer and more authentic community through proactive harm prevention, strong identity trust, and empowering users in their safety experiences, all while adapting to evolving regulatory standards. This high-impact role sits at the crossroads of AI/ML, fraud prevention, risk management, and trust & safety, spearheading strategies and innovations that ensure authenticity, curtail harmful behaviors, and bolster global user confidence.
We seek a technically adept, inquisitive individual eager to broaden their product acumen and analytical leadership. You will be a pivotal member of Grindr’s centralized Data organization, which unites data scientists, data engineers, and ML/AI engineers in a collaborative environment. This role offers the chance to expand your influence while learning from diverse colleagues.
At Grindr, we embody the Grindr Mode philosophy: we work diligently yet prioritize well-being. We value outcomes over outputs, and our team consists of intelligent, driven individuals who elevate each other's standards while allowing for a balanced life.
About the Job:
Define and track key product metrics alongside cross-functional partners.
Design, execute, and analyze A/B tests to assess the impact of new features.
Conduct in-depth data analyses to clarify trends and reveal actionable insights.
Effectively communicate findings to stakeholders and influence product strategies.
Develop dashboards and tools to assist teams in monitoring metrics and making data-driven decisions.
Contribute to the establishment of best practices within the Data Science team.

