We’re looking for an experienced Data Scientist to join our Rides Safety team and help build our predictive and automated safety and risk systems - from user screening tooling and telemetry anomaly detection to behaviour factors predictions.

If you're excited about applying machine learning and automated decision-making tools to real-world mobility challenges, you’ll find plenty of impactful work here.

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!

You'll own Bolt's Safety automation and prediction systems end-to-end and directly influence users from our marketplace with millions of trips daily, working in an independent and self-sufficient full stack product team - from mobile applications through the server infrastructure. Your daily tasks will range from modelling risk to designing and experimenting with automated intervention strategies. This includes managing the load on automation endpoints and real-time data streams. You’ll identify new safety opportunities, run large-scale experiments, and take predictive and automation models from research to production. This is a highly impactful role where your work will directly shape the experience of over 200 million customers worldwide.

• Identify, research, and prioritise hypotheses to improve automated and predictive safety algorithms (e.g., risk scoring, verification, and progressive interruption systems).
• Develop, deploy, and monitor automated safety systems, ranging from classical supervised learning to real-time risk models and advanced control system designs.
• Design and run large-scale experiments to validate safety approaches and estimate their impact on core safety metrics (e.g., incident rates, verification success, and driver/rider experience).
• Lead the data science and ML-first approach to safety and risk management in the company.
• Partner with analysts, engineers, product managers, and operations specialists to identify safety problems and develop the most efficient, data-informed solutions.

• Strong ownership mindset and comfort working autonomously from problem research to model deployment.
• 3+ years of experience in machine learning for automated decision making.
• Exceptional knowledge of machine learning algorithms, statistical inference, and autonomous decision-making systems.
• Mastery in Python and SQL.
• Skilled at communication with cross-functional stakeholders.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

We’re looking for an experienced Data Scientist to join our Rides Safety team and help build our predictive and automated safety and risk systems - from user screening tooling and telemetry anomaly detection to behaviour factors predictions.

If you're excited about applying machine learning and automated decision-making tools to real-world mobility challenges, you’ll find plenty of impactful work here.

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!

You'll own Bolt's Safety automation and prediction systems end-to-end and directly influence users from our marketplace with millions of trips daily, working in an independent and self-sufficient full stack product team - from mobile applications through the server infrastructure. Your daily tasks will range from modelling risk to designing and experimenting with automated intervention strategies. This includes managing the load on automation endpoints and real-time data streams. You’ll identify new safety opportunities, run large-scale experiments, and take predictive and automation models from research to production. This is a highly impactful role where your work will directly shape the experience of over 200 million customers worldwide.

• Identify, research, and prioritise hypotheses to improve automated and predictive safety algorithms (e.g., risk scoring, verification, and progressive interruption systems).
• Develop, deploy, and monitor automated safety systems, ranging from classical supervised learning to real-time risk models and advanced control system designs.
• Design and run large-scale experiments to validate safety approaches and estimate their impact on core safety metrics (e.g., incident rates, verification success, and driver/rider experience).
• Lead the data science and ML-first approach to safety and risk management in the company.
• Partner with analysts, engineers, product managers, and operations specialists to identify safety problems and develop the most efficient, data-informed solutions.

• Strong ownership mindset and comfort working autonomously from problem research to model deployment.
• 3+ years of experience in machine learning for automated decision making.
• Exceptional knowledge of machine learning algorithms, statistical inference, and autonomous decision-making systems.
• Mastery in Python and SQL.
• Skilled at communication with cross-functional stakeholders.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!