Senior Data Scientist
Blacklane
YOUR CHALLENGE:
As a Senior Data Scientist within Blacklane's central data domain, you will leverage scientific and mathematical methodologies to address complex data challenges prevalent in the mobility and luxury transportation sector. In this role, you will also play a key part in scaling the data science team by owning and evolving our machine learning platform and operating model. This role involves close collaboration with product, engineering, and other data teams to enhance profitability, optimize costs, and accelerate growth. You will also engage with diverse business stakeholders globally. Beyond individual use cases, you will be responsible for how machine learning solutions move from idea to production and remain reliable over time. This position provides avenues for continuous professional development, flexible work options, and participation in an inclusive and diverse work environment.
- Design, build, and maintain end-to-end machine learning systems, supporting use cases such as demand forecasting, pricing optimization, customer lifetime value, and churn prediction.
- Establish best practices for experimentation, reproducibility, and model evaluation, while analyzing complex datasets to uncover trends, patterns, and actionable insights.
- Collaborate with cross-functional teams to understand business needs and translate them into scalable scientific and machine learning solutions.
- Collaborate with stakeholders at various levels to propose, discuss, and drive scalable data science solutions, clearly communicating tradeoffs and impact.
- Design and evolve shared ML pipelines, tooling, and standards to enable the team to scale efficiently and safely
ABOUT YOU:
- Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, or a related field.
- Minimum 5 years of experience in a data science or machine learning engineering role.
- Proven track record in designing and deploying machine learning models into production environments, especially using AWS services (e.g. SageMaker, EC2, S3, Lambda, Step Functions).
- Experience working with cloud-based ML platforms (e.g. AWS SageMaker or equivalent services).
- Demonstrated proficiency in modeling business problems through the application of machine learning techniques, including feature engineering, model selection, implementation, evaluation, and parameter tuning.
- Ability to translate business challenges into mathematical and statistical problems, subsequently proposing and implementing data science solutions.
- Strong judgment in selecting appropriate models and designing systems that balance accuracy, reliability, and scalability.
- Hands-on experience with modern data science tools and ML frameworks, combined with experience building or improving shared ML pipelines and tooling.
- Strong analytical and problem-solving capabilities, with the aptitude to interpret complex datasets.
- Strong experience operationalizing machine learning systems end to end, including CI/CD, automation, monitoring, and retraining.
- Exceptional communication skills, with a collaborative mindset and experience influencing technical direction across teams
- Self-driven, curious, and proactive in staying current with developments in ML, MLOps, and cloud computing.
About Blacklane
Our mission is simple but powerful: to become the world’s leading premium, global chauffeur service. Operating in 50+ countries, we reimagine chauffeur-driven rides by prioritizing reliability, innovation, and first-class service at every step. Blacklane is also at the forefront of sustainable mobility efforts, continuously working to reduce our operational impact on the planet.
Our Company Culture
Blacklane has grown from a two-person startup in Berlin to a global team of over 300 people representing 54+ nationalities. Powered by our commitment to care, inclusion, innovation, and collaboration, we support employees through initiatives like Employee Resource Groups (ERGs), mentorship programs, and more.
Here are just a few examples of the ERGs fostering connection:
- LGBTQIA+ Network – Advocating for inclusivity and championing allyship.
- Bookclub – Encouraging cultural exchange, fostering discussion, critical thinking, and team engagement through shared reading and analysis.
- Blacklane Cares Leave – Spend up to eight paid hours annually volunteering for causes meaningful to you.
We welcome—and actively support—employees to create or join the communities that are important to them.
✨ Why join Blacklane?
At Blacklane, our Compensation and Benefits strategies are designed to be fair and market-aligned. We combine base salary with variable elements and long-term incentives as part of our overall rewards framework. All employees participate in our company-wide Virtual Stock Option Plan (VSOP), sharing in Blacklane’s long-term success.
In addition, we offer a benefits package tailored to each location, supporting health, wellbeing, time off, learning, and local needs. Some of the benefits for this role and country include:
Local perks – UK (London)
💙 100% employer-paid health insurance for you and your dependents, with 24hr GP access
🌴 28 vacation days per year, increasing with tenure
🏦 Company pension with up to 5% employer contribution
🍽️ Twice‑weekly Just Eat lunch vouchers for UK hub employees
💪 Your Mental and Physical Health → No compromise with Nilo and Wellhub
🎓 Continuous learning & certified coaching
🏢 Hybrid setup: 3 days a week in our London office
🚀 Fair pay and shared success through our VSOP program
🚘Mystery Rides: Quarterly Voucher to enjoy personal trips around the world with Blacklane and experience our service from a guest’s perspective.
Do you have any questions or want to know more about our way of working? Feel free to contact us. We’re happy to connect!
We place great value on equal opportunities. Therefore, we welcome everyone to apply!
Curious to see us in action? Let’s go!
→ Watch us on Amazon Prime
→ Listen to our CEO in Startup insider episode #1643
→ Blacklane is backed by investors who share our vision: Mercedes-Benz Mobility, Tasaru, Sixt, the Al Fahim Group, Alstin Capital, RI Digital Ventures, and b2venture