Senior Data Scientist

We’re looking for a Senior Data Scientist to join Bolt’s Rides Matching domain. You’ll use data to uncover opportunities, frame the right questions, and shape how we verify match drivers and dispatch offers to them. Your work will directly influence marketplace balance, growth, and user experience.

About Us

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

About The Role

Matching is the core of Bolt’s ride-hailing and powers efficient, data-driven, high-scale matching in hundreds of cities across the globe. You’ll lead discovery analyses across search, dispatching, and matching, translate patterns into hypotheses, and partner with product and engineering to design experiments and data-driven changes. Expect to prototype lightweight models where they’re the simplest, highest-leverage tool, keeping the emphasis on problem-finding, evidence, and impact.

Main tasks and responsibilities:

• Probe matching funnels to find friction and opportunity, size the impact, and turn insights into prioritized, testable ideas.
• Design and analyze A/B tests, and deliver crisp readouts with recommended decisions.
• Prototype lightweight models and decision rules with careful offline/online evaluation and simple monitoring; collaborate with engineers for productionization.
• Discover and evaluate new marketplace efficiency features (what drivers to match with, when to match, how long, batch them or not) that improve marketplace efficiency and matching speed; articulate trade-offs and expected impact clearly to stakeholders.
  
  
  

About you:

• 2-5 years in a data-science or quantitative product role, with strong statistical thinking and curiosity for problem discovery.
• Proficient in SQL and Python (Pandas/NumPy; scikit-learn for light modeling); experienced in working with large datasets and communicating trade-offs clearly.
• Hands-on with experimentation and with causal/observational reasoning when randomized tests aren’t feasible.
• Comfortable turning ambiguous spaces into measurable metrics, hypotheses, and shipped improvements; you default to the simplest approach that moves the needle.
  
  
  

Experience is great, but we also look for drive, intelligence, and integrity. So, even if you don’t tick every box, please consider applying if you feel you’re the kind of person described above!