At a Glance
- Tasks: Design and maintain machine learning systems to solve complex data challenges in luxury transport.
- Company: Join Blacklane, a global leader in premium chauffeur services with a diverse team.
- Benefits: Enjoy 28 vacation days, health insurance, hybrid work, and continuous learning opportunities.
- Why this job: Make a real impact in the mobility sector while working with cutting-edge technology.
- Qualifications: 5+ years in data science, strong ML skills, and experience with AWS services required.
- Other info: Inclusive culture with support for employee communities and career growth.
The predicted salary is between 48000 - 72000 £ per year.
As a Senior Data Scientist within Blacklane's central data domain, you will leverage scientific and mathematical methodologies to address complex data challenges in the mobility and luxury transportation sector. In this role, you will help scale the data science team by owning and evolving our machine learning platform and operating model. You will collaborate closely with product, engineering, and other data teams to enhance profitability, optimize costs, and accelerate growth. You will engage with diverse business stakeholders globally, and 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.
Qualifications
- 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 prioritising 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.
Benefits
- 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
We welcome—and actively support—employees to create or join the communities that are important to them. We place great value on equal opportunities. Therefore, we welcome everyone to apply. Do you have any questions or want to know more about our way of working? We’re happy to connect!
Senior Data Scientist London employer: Blacklane
Contact Detail:
Blacklane Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist London
✨Tip Number 1
Network like a pro! Reach out to current employees at Blacklane on LinkedIn or through mutual connections. A friendly chat can give you insider info and might even lead to a referral, which is always a bonus!
✨Tip Number 2
Prepare for the interview by brushing up on your machine learning knowledge. Be ready to discuss your past projects and how you've tackled complex data challenges. Show them you’re not just a data whiz but also a great communicator who can collaborate with cross-functional teams.
✨Tip Number 3
Don’t forget to showcase your passion for continuous learning! Mention any recent courses or certifications you've completed in data science or machine learning. This shows you're proactive and committed to staying ahead in the field.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Blacklane team. Good luck!
We think you need these skills to ace Senior Data Scientist London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with machine learning models, AWS services, and any relevant projects that showcase your skills in data science.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for Blacklane. Share specific examples of how you've tackled complex data challenges and collaborated with cross-functional teams in the past.
Showcase Your Technical Skills: Don’t forget to mention your hands-on experience with modern data science tools and ML frameworks. We want to see how you’ve operationalised machine learning systems and your approach to model evaluation.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Blacklane!
How to prepare for a job interview at Blacklane
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning concepts and methodologies. Be ready to discuss your experience with AWS services like SageMaker and how you've deployed models in production. They’ll want to see that you can translate complex data challenges into actionable solutions.
✨Showcase Your Collaboration Skills
Since this role involves working closely with product, engineering, and other teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight your ability to communicate technical concepts clearly to non-technical stakeholders.
✨Prepare for Technical Questions
Expect some deep dives into your technical expertise. Brush up on your knowledge of model evaluation, feature engineering, and CI/CD processes. Practise explaining your thought process when solving data problems, as they’ll want to see your analytical skills in action.
✨Demonstrate Your Passion for Continuous Learning
Blacklane values self-driven individuals who stay current with developments in ML and cloud computing. Be ready to discuss any recent projects or courses you've undertaken to enhance your skills. Show them that you're proactive about your professional development!