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- Tasks: Train, deploy, and evaluate cutting-edge fraud detection models using machine learning.
- Company: Join Ravelin, a fun and friendly fraud detection company with a strong culture.
- Benefits: Flexible hours, health insurance, wellness budget, and generous holiday time.
- Why this job: Make online transactions safer while working with brilliant minds in tech.
- Qualifications: Experience in ML model building and strong analytical skills required.
- Other info: Enjoy team lunches, board game nights, and opportunities to give back.
The predicted salary is between 28800 - 48000 £ per year.
Who are we? Hi! We are Ravelin! We're a fraud detection company using advanced machine learning and network analysis technology to solve big problems. Our goal is to make online transactions safer and help our clients feel confident serving their customers. We are a friendly bunch and pride ourselves in having a strong culture and adhering to our values of empathy, ambition, unity and integrity. We really value work/life balance and we embrace a flat hierarchy structure company-wide. Join us and you’ll learn fast about cutting-edge tech and work with some of the brightest and nicest people around.
The Team You will be joining the Detection team. The Detection team is responsible for keeping fraud rates low – and clients happy – by continuously training and deploying machine learning models. We aim to make model deployments as easy and error free as code deployments. Our models are trained to spot multiple types of fraud, using a variety of data sources and techniques in real time. The prediction pipelines are under strict SLAs, every prediction must be returned in under 300ms. When models are not performing as expected, it’s down to the Detection team to investigate why. The Detection team is core to Ravelin’s success. They work closely with the Data Engineering Team who build infrastructure and the Intelligence & Investigations Team who liaise with clients.
The Role We are currently looking for a Data Scientist to help train, deploy, debug and evaluate our fraud detection models. Our ideal candidate is pragmatic, approachable and filled with knowledge tempered by past failures. Evaluating fraud models is hard; often times we do not even get labels for 3 months. You’ll need to use your judgement when investigating cases of ambiguous fraud and when you’re investigating the veracity of the model itself. We have to build robust models that are capable of updating their beliefs when they encounter new methods of fraud: our clients expect us to be one step ahead of fraud, not behind. You will be given the equipment, space and guidance you need to build world class fraud detection models. The work is not all green field research. The everyday work is about making safe incremental progress towards better models for our clients. The ideal candidate is willing to get involved in both aspects of the job – and understand why both are important.
Responsibilities:
- Build out our model evaluation and training infrastructure.
- Develop and deploy new models to detect fraud whilst maintaining SLAs.
- Write new features in our production infrastructure.
- Research new techniques to disrupt fraudulent behaviour.
- Investigate model performance issues (using your experience of debugging models).
- Mentor junior members of the team.
Requirements:
- Significant experience building and deploying ML models using the Python data stack (numpy, pandas, sklearn).
- Understand software engineering best practices (version control, unit tests, code reviews, CI/CD) and how they apply to machine learning engineering.
- Strong analytical skills.
- Being a strong collaborator with colleagues outside of your immediate team, for example with client support teams or engineering.
- Being skilled at communicating complex technical ideas to a range of audiences.
- The ability to prioritise and to manage your workload.
- Being comfortable working with a hybrid team.
Nice to haves:
- Experience with Docker, Kubernetes and ML production infrastructure.
- Tensorflow and deep learning experience.
- Experience using dbt.
- Experience with Go, C++, Java or another systems language.
Benefits:
- Flexible Working Hours & Remote-First Environment — Work when and where you’re most productive, with flexibility and support.
- Comprehensive BUPA Health Insurance — Stay covered with top-tier medical care for your peace of mind.
- £1,000 Annual Wellness and Learning Budget — Prioritise your health, well-being and learning needs with funds for fitness, mental health, and more.
- Monthly Wellbeing and Learning Day — Take every last Friday of the month off to recharge or learn something new, up to you.
- 25 Days Holiday + Bank Holidays + 1 Extra Cultural Day — Enjoy generous time off to rest, travel, or celebrate what matters to you.
- Mental Health Support via Spill — Access professional mental health services when you need them.
- Aviva Pension Scheme — Plan for the future with our pension program.
- Ravelin Gives Back — Join monthly charitable donations and volunteer opportunities to make a positive impact.
- Fortnightly Randomised Team Lunches — Connect with teammates from across the company over in person or remote lunches every other week on us!
- Cycle-to-Work Scheme — Save on commuting costs while staying active.
- BorrowMyDoggy Access — Love dogs? Spend time with a furry friend through this unique perk.
- Weekly Board Game Nights & Social Budget — Unwind with weekly board games or plan your own socials, supported by a company budget.
Data Scientist (Mid level) in London employer: Ravelin
Contact Detail:
Ravelin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Mid level) in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Ravelin on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. It’s a great way to get insider info and show your genuine interest in the company.
✨Tip Number 2
Prepare for technical interviews by brushing up on your ML models and Python skills. Practice explaining your past projects and how you tackled challenges. Remember, they want to see your thought process, so be ready to discuss your approach to debugging and model evaluation.
✨Tip Number 3
Show off your collaborative spirit! Ravelin values teamwork, so be prepared to share examples of how you've worked with others in the past. Highlight any cross-team projects or mentoring experiences to demonstrate your ability to communicate complex ideas effectively.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the Ravelin team. Good luck, and we can’t wait to see your application!
We think you need these skills to ace Data Scientist (Mid level) in London
Some tips for your application 🫡
Show Your Passion: When you're writing your application, let your enthusiasm for data science and fraud detection shine through! We want to see that you’re genuinely excited about the role and how you can contribute to our mission of making online transactions safer.
Tailor Your CV: Make sure your CV is tailored to the job description. Highlight your experience with machine learning models, Python, and any relevant projects. We love seeing how your skills align with what we do at Ravelin!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to explain your experience and skills. We appreciate a well-structured application that makes it easy for us to see why you’d be a great fit for the team.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Ravelin
✨Know Your Stuff
Make sure you brush up on your machine learning models and the Python data stack. Be ready to discuss your past experiences with deploying models, debugging issues, and how you've tackled ambiguous fraud cases. Ravelin values practical knowledge, so be prepared to share specific examples.
✨Show Your Collaborative Spirit
Ravelin prides itself on a friendly culture and teamwork. Highlight your experience working with cross-functional teams, especially with client support or engineering. Share stories that demonstrate your ability to communicate complex ideas clearly and effectively.
✨Embrace the Challenge
The role involves investigating model performance issues and adapting to new fraud methods. Show your problem-solving skills by discussing how you've approached similar challenges in the past. Be ready to explain your thought process and how you prioritise tasks under pressure.
✨Cultural Fit Matters
Ravelin values empathy, ambition, unity, and integrity. During the interview, reflect these values in your responses. Share how you align with their mission of making online transactions safer and how you can contribute to their positive work environment.
