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For Companies At a Glance
- Tasks: Lead impactful data projects and develop machine learning models to drive business success.
- Company: Zopa Bank, a pioneer in peer-to-peer lending with a people-first approach.
- Benefits: Hybrid work model, flexibility to work abroad, and a supportive team environment.
- Why this job: Make a real difference in finance while working with cutting-edge technology and innovative teams.
- Qualifications: Strong Python skills and a passion for solving complex data problems.
- Other info: Join a diverse team committed to creating a rich company culture.
The predicted salary is between 43200 - 72000 £ per year.
We built the first peer‑to‑peer lending company in 2005 and launched Zopa Bank in 2020. We believe in putting people first and are redefining what it feels like to work in finance. We employ advanced machine learning techniques across over seven years of experience in consumer finance.
Responsibilities
- Lead high‑impact data and modelling projects across marketing, customer engagement, credit risk, fraud detection and pricing.
- Own the full project lifecycle: identify business opportunities, curate and process data, engineer features, develop machine learning models, deploy to production and monitor performance.
- Engage with senior stakeholders to influence critical business decisions and deliver direct impact on products and millions of customers.
- Collaborate daily with product managers, analysts, data engineers and software engineers to progress projects.
- Support other data scientists through knowledge sharing, code reviews, and developing common utilities and infrastructure.
Qualifications
- Passion for data and a proven track record of solving complex problems to deliver business value.
- Curious, innovative, with a willingness to challenge the status quo.
- Strong communicator who can influence decision makers and build trust across stakeholders.
- Team player with a can‑do attitude and commitment to getting the job done.
- Excellent Python skills and familiarity with Git, Docker, CI/CD and REST APIs.
- In‑depth knowledge of machine learning algorithms (e.g., logistic regression, random forest, gradient‑boosted trees, neural networks, k‑means) and statistics (Monte Carlo, hypothesis testing, confidence intervals, maximum likelihood, bootstrap, Bayesian inference).
Bonus Skills
- Experience with causal inference modelling.
- Domain knowledge of consumer lending or credit risk.
- Experience building and deploying generative AI systems.
- People‑management experience.
Working Arrangements
- Hybrid role: attend the London office 2–3 days a week. Option to work from abroad for up to 120 days a year, subject to work‑right requirements.
Diversity Statement
Zopa is proud to offer a workplace free from discrimination. We recognise that diverse experience, perspectives and backgrounds create better products and a richer company culture. We provide reasonable adjustments throughout the hiring process. We may use AI tools to support parts of the recruitment process, but final hiring decisions are made by humans. If you would like more information about how your data is processed, please let us know.
Senior Data Scientist employer: Zopa Bank
Contact Detail:
Zopa Bank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees at Zopa Bank on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Prepare for the interview by brushing up on your Python skills and machine learning algorithms. Be ready to discuss how you've tackled complex problems in the past, as this will show your passion for data and problem-solving.
✨Tip Number 3
Show off your collaborative spirit! During interviews, highlight experiences where you've worked with cross-functional teams. Zopa values team players, so make sure they see that you're all about collaboration.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Zopa family.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let your enthusiasm for data shine through! Share specific examples of how you've tackled complex problems and delivered real business value. We love seeing candidates who are genuinely excited about the impact of their work.
Tailor Your Application: Make sure to customise your application to highlight your relevant skills and experiences that align with the Senior Data Scientist role. Mention your expertise in machine learning algorithms and any experience you have in consumer lending or credit risk. This helps us see how you fit into our team!
Communicate Clearly: Strong communication is key in our collaborative environment. Use your application to demonstrate how you've influenced decision-makers and built trust with stakeholders in past roles. We want to know how you can engage with our team and contribute to impactful projects.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows us you're keen to join the Zopa family!
How to prepare for a job interview at Zopa Bank
✨Know Your Data Inside Out
As a Senior Data Scientist, you’ll need to demonstrate your deep understanding of data and machine learning algorithms. Brush up on key concepts like logistic regression and neural networks, and be ready to discuss how you've applied these in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex problems you've solved in the past. Highlight how your solutions delivered business value, especially in areas like credit risk or fraud detection, as this will resonate with Zopa's focus.
✨Engage with Stakeholders
Since influencing decision-makers is crucial, practice articulating your ideas clearly and confidently. Think about how you can build trust with stakeholders and prepare to discuss how you've successfully collaborated with product managers and engineers in previous roles.
✨Be Ready for Technical Questions
Expect technical questions that test your Python skills and familiarity with tools like Git and Docker. Brush up on your coding skills and be prepared to solve problems on the spot, as this will showcase your hands-on expertise.
