Data Scientist
Bumble Inc. is looking for a Data Scientist to join our Core Data Science team — helping to uncover the drivers of member behaviour and performance across our products. You’ll play a key role in shaping how we understand and segment our members, providing insights that directly inform product strategies and answer key business questions.
This role is ideal for someone who’s passionate about applying analytical thinking to commercial problems. You’ll use Python, SQL, and statistical or machine learning techniques to uncover insights, build models, and make data accessible and actionable for business partners.
If you’re curious, commercially minded, and thrive in a collaborative environment where data drives decisions, we’d love to hear from you.
KEY ACCOUNTABILITIES
- Partner with commercial, product, and finance teams to define and investigate key business questions related to revenue growth and member behaviour.
- Develop and maintain member behavioural segmentations that help the business better understand and serve different user groups.
- Use data to identify patterns, opportunities, and risks within revenue and engagement metrics.
- Apply statistical and machine learning techniques (e.g., clustering, regression, classification) to support segmentation, and performance diagnostics.
- Translate complex analytical outputs into clear, commercially relevant insights and recommendations for decision-makers.
- Collaborate with data engineering and analytics teams to ensure data quality and reliable reporting foundations.
- Contribute to the development of measurement frameworks that evaluate the impact of pricing, product, and business initiatives.
- Help build a data-informed culture by communicating insights in an engaging, strategic, and actionable way.
EXPERIENCE WE ARE LOOKING FOR
- 2–4 years of experience in a data science, analytics, or strategy role — ideally within a technology, subscription, or digital platform business.
- Strong Python and SQL skills for data manipulation, modeling, and automation.
- Experience applying machine learning or statistical methods to real-world business problems (e.g., clustering, regression, or propensity modeling).
- Proven ability to connect analytics to commercial outcomes — you think in terms of impact, trade-offs, and growth opportunities.
- Experience developing or using customer or behavioural segmentation frameworks.
- Skilled in data visualisation and storytelling, using tools such as Looker, Tableau.
- Excellent communicator with the ability to work cross-functionally and translate analytical findings into business language.
- A collaborative problem-solver with a curiosity for understanding how data influences business performance.
