Senior Staff Data Scientist, Grindr

• BS or higher in Computer Science, Statistics, Mathematics, Physics, a related quantitative field, or equivalent experience
• 10+ years of industry data science experience, with a track record of influencing senior stakeholders and company-level outcomes
• 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

• As a Senior Staff Data Scientist at Grindr, you will lead cross-functional collaboration with product managers, product designers, and engineers to devise insightful metrics that guide development, shape and oversee novel experiments, present a data-driven viewpoint to guide key decisions, and identify and drive new strategic avenues for 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, tea
• Extract actionable insights from broad, open-ended questions
• Set strategy for designing and evaluating experiments to measure the impact of product changes
• Influence and communicate results to executives and cross-functional stakeholders to inform product and company decisions
• Analyze data from across the product to uncover the root causes of metric movements
• Communicate results to cross-functional stakeholders to inform product decisions
• Architect and guide development of 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
• Shape the future state of our data products, devising ML solutions to improve recommendations, detect spam, and better serve our users