At a Glance
- Tasks: Design and maintain machine learning systems to solve complex data challenges.
- Company: Join Blacklane, a global leader in premium chauffeur services.
- Benefits: Enjoy 28 vacation days, health insurance, and hybrid work options.
- Why this job: Make a real impact in the luxury transportation sector with innovative data solutions.
- Qualifications: 5+ years in data science, strong ML skills, and cloud experience required.
- Other info: Be part of a diverse team committed to sustainability and continuous learning.
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.
Responsibilities:
- 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 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.
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 problem-solving skills! During interviews, be prepared to walk through your thought process when faced with a tricky data issue. This will highlight your analytical capabilities and how you approach real-world problems.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows your genuine interest in joining the Blacklane team. Let’s get you that Senior Data Scientist role!
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 and any relevant projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to Blacklane's mission. Be sure to mention specific experiences that relate to the job description.
Showcase Your Technical Skills: Don’t forget to highlight your technical skills, especially your experience with AWS services and machine learning frameworks. We love seeing hands-on experience, so include any relevant tools or technologies you've used in your previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
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 data teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight your ability to communicate technical concepts to non-technical stakeholders and how you’ve influenced decisions across teams.
✨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. You might be asked to solve a problem on the spot, so practice explaining your thought process clearly and logically.
✨Demonstrate Your Passion for Continuous Learning
Blacklane values self-driven individuals who stay current with developments in ML and cloud computing. Share any recent projects, courses, or conferences you've attended that showcase your commitment to professional growth. This will show them you're proactive and eager to contribute to their innovative environment.