At a Glance
- Tasks: Lead Data Science teams to optimise financial wellbeing products and drive impactful projects.
- Company: Join a fast-growing fintech company making a real difference in people's financial lives.
- Benefits: Enjoy 25 days holiday, hybrid working, and generous perks including health and wellness support.
- Why this job: Shape the future of financial wellbeing while mentoring a passionate team in a collaborative environment.
- Qualifications: 5+ years in Data Science, strong leadership skills, and proficiency in Python and SQL.
- Other info: Be part of a diverse team committed to making a positive societal impact.
The predicted salary is between 48000 - 72000 £ per year.
Working with employers, we provide a financial wellbeing platform as an employee benefit, helping employees to understand their money better, get out of debt faster and save for their future. We already have a reach of circa 4,000,000 employees through our relationships with over 500 of the largest employers in the UK. By improving employee financial wellbeing, we have a very real and meaningful impact on people’s lives. We remove the stress and worry associated with financial difficulties by dramatically reducing the interest rates employees pay on their personal debt, and provide them with the tools needed to start saving sooner and be more financially secure.
Your role in our mission: We are looking for an exceptional Data Science Manager to lead our Data Science and Decision Systems teams. Reporting to the Chief Product Officer, you will be responsible for shaping strategy and mentoring the team, while remaining hands-on with project delivery. In 2026, you and the team will focus on optimising our core lending product. You will work closely with the Credit Risk and Collections teams to deliver new scorecards, build collections models, and refactor our decision engine - initiatives that contribute directly to improving our unit economics and scalability. From 2027, the focus will shift to expansion and innovation. As the team grows to support other parts of the business, your role will evolve into a more managerial position focused on setting strategy and supporting team members. Your stakeholder set will also broaden to include Product, Engineering, and Enterprise Data teams as you tackle topics such as marketing attribution, predictive models for our wider product set, and defining new measures for customer financial wellbeing.
What you’ll do:
- Lead the delivery of our Data Science roadmap, including the development of new credit risk scorecards, collections models, and the refactoring of our Decision Engine.
- Initially dedicate ~50% of your time to hands-on delivery (modelling and analysis), with this proportion decreasing as the team and scope expand in 2027.
- Own the architecture and deployment processes for the Decision Engine, ensuring high availability, minimising operational risk, and managing technical debt.
- Introduce and enforce best practices in modelling, engineering, and governance to ensure technical excellence across the Data Science team.
- Provide expert mentorship to the team, fostering individual growth and helping them navigate complex technical challenges.
- Promote a data-driven approach to problems across the business, championing the Data Science team through excellent communication.
- Collaborate with Credit Risk, Collections, and Product stakeholders to translate business objectives into technical requirements.
- Shape the future strategy for the Data Science function, preparing the team to pivot toward marketing attribution and financial wellbeing innovation in the long term.
About you:
- Experience: You have 5+ years of experience in Data Science or similar analytical roles, with a proven track record of delivering value, preferably in financial services and/or credit risk.
- Leadership: You have experience managing teams and you are capable of mentoring juniors and representing Data Science to senior stakeholders.
- Production-grade Python: You write clean, modular code and are comfortable building production-grade systems in Python.
- Data & SQL proficiency: You are highly skilled in SQL, capable of extracting and processing data to derive actionable insights.
- Engineering best practices: You are experienced with version control (Git), Docker and CI/CD pipelines.
- Communication & influence: You can explain complex technical concepts to non-technical stakeholders (like Product and Commercial teams) and advocate for the best data solutions.
Nice to have:
- R language skills: Our existing decision engine is written in R. The ability to read and interpret R code will be valuable as you lead the refactoring effort into Python.
- Scale-up experience: You have succeeded in fast-paced scale-up environments.
- Model governance: You have had experience with setting up or managing formal model governance frameworks (e.g. model monitoring, documentation standards).
- Deep Learning and AI: You are well-versed in LLMs and GenAI, and know how to best apply their use to drive business value.
Who you are: We embrace our differences, but there’s one thing we like to share, which is our values, so it’s important to us that you are:
- Fearless, and able to make the impossible possible.
- Responsible, and want to help build a business that delivers a meaningful difference to society.
- Dedicated and want to commit to an exciting journey even through the highs and lows.
- Empathetic and truly care about every colleague and customer.
- United, because you understand we achieve more when we work as a team.
- Humble, and take feedback as a way to continuously improve.
What do you get for all your hard work?
- 25 days holiday with an additional day off for every year of service up to 30 days and an extra day off on your birthday.
- Hybrid working arrangements so you can work from the office and from home with a budget to help you get set up.
- Generous company benefits to include pension and life assurance and an annual allowance to spend on medical insurance, health cash plan, denplan, gym memberships.
- Enhanced policies that are family and pet friendly, to include company sick pay and peternity leave.
- Great career development in a fast-paced environment.
- Regular company socials (post covid, although we’ve got quite good at virtual ones too!).
- Volunteer days as part of our CSR program.
- More great perks to include weekly snacks, tuckshop, cycle to work, help to save and much more!
The typical interview process:
- Introductory call with our Talent Manager (phone call - 20 mins).
- Past experience interview with Hiring Manager (video call - 30 mins).
- Technical and culture interview with Team and Stakeholder(s) (in person - 2 hours).
We’re looking for people that will get stuck in and make a difference. We have a great collaborative, entrepreneurial team and are passionate about what we do. If you want to join a team that is changing people’s lives for the better then we’d love to hear from you.
Salary Finance is proud to be an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive work environment where all employees and applicants can flourish.
Data Science Manager employer: Salary Finance
Contact Detail:
Salary Finance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage on platforms like LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Prepare for those interviews! Research the company, understand their mission, and be ready to discuss how your skills align with their goals. We want to see you shine, so practice common interview questions and have your own ready to ask too!
✨Tip Number 3
Showcase your projects! Whether it's through a portfolio or a GitHub repository, let us see your work. Highlighting your hands-on experience with data science projects can really set you apart from the crowd.
✨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, we love seeing candidates who are genuinely interested in joining our mission to improve financial wellbeing.
We think you need these skills to ace Data Science Manager
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Science Manager role. Highlight your relevant experience in data science, especially in financial services, and showcase how your skills align with our mission at StudySmarter.
Showcase Your Technical Skills: We want to see your technical prowess! Be sure to mention your experience with Python, SQL, and any other relevant tools. If you've worked on production-grade systems or have experience with model governance, shout about it!
Communicate Clearly: Remember, you’ll need to explain complex concepts to non-technical stakeholders. Use clear, straightforward language in your application to demonstrate your communication skills and ability to bridge the gap between tech and business.
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 the role. Plus, it shows you’re keen to join our team at StudySmarter!
How to prepare for a job interview at Salary Finance
✨Know Your Data Science Stuff
Make sure you brush up on your data science skills, especially in Python and SQL. Be ready to discuss your past projects and how you've used data to drive decisions. They’ll want to see that you can not only talk the talk but also walk the walk when it comes to hands-on modelling and analysis.
✨Showcase Your Leadership Skills
As a Data Science Manager, you'll need to demonstrate your ability to lead and mentor a team. Prepare examples of how you've successfully managed teams in the past, and be ready to discuss your approach to fostering individual growth and navigating complex challenges.
✨Communicate Like a Pro
You’ll be working with non-technical stakeholders, so practice explaining complex concepts in simple terms. Think about how you can advocate for data-driven solutions while ensuring everyone understands the value behind them. Clear communication is key!
✨Align with Their Mission
Familiarise yourself with the company's mission of improving financial wellbeing. Be prepared to discuss how your experience aligns with their goals and how you can contribute to making a meaningful impact on people's lives through data science.