Staff Data Scientist, Grindr

• BS or higher in Computer Science, Statistics, Mathematics, Physics, a related quantitative field, or equivalent experience
• 7+ years of industry data science experience
• Experience effectively communicating & collaborating with non-technical stakeholders
• A deep understanding of the “why” behind your work, not just the how
• Strong Python skills in data analysis using pandas and Jupyter Notebook
• Experience writing and optimizing complex SQL queries on large data sets
• A strong background in inferential statistics, especially in an experimentation setting (hypothesis testing, power analysis, experimental design)
• Experience with different data analytics and BI tools such as Looker, Tableau, PowerBI, or Snowflake
• Experience in big data technologies like Spark

Desirable

• Grindr (NYSE: GRND) is the largest LGBTQ+ Social App in the world, used by over 14M+ monthly users in nearly every country in the world. We are a fundamental part of the global LGBTQ+ community and are a pillar in gay culture
• As a Staff Data Scientist at Grindr, you will be working closely with product managers, product designers, and engineers to devise insightful metrics that guide development, design and execute novel experiments, present a data-driven viewpoint to guide key decisions, and find new avenues to drive growth through deep dive analysis
• You will have the opportunity to work on models that are deployed to production and improve quality of life for our millions of users
• You will also be an informal ambassador for the Data Science team to the rest of the organization, educating a diverse group on the many subtle aspects of utilizing data well
• You will be a member of the data organization at Grindr, which integrates data scientists, data engineers, and ML/AI engineers into a single cohesive and collaborative team
• This is a rare opportunity to learn, teach, and have an outsized impact alongside some of the top minds in the field
• Extract actionable insights from broad, open-ended questions
• Design and evaluate experiments to measure the impact of product changes
• Analyze data from across the product to uncover the root causes of metric movements
• Communicate results to cross-functional stakeholders to inform product decisions
• Develop tools to scale and automate analyses, improving productivity across the company
• Provide mentorship and guidance to team members + identify and recommend best practices
• Apply an engineering mindset: minimize complexity while maximizing utility & maintainability
• Be part of building our future state, devising ML solutions to improve recommendations, detect spam, and better serve our users