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- Tasks: Transform complex data into insights and models that drive business decisions.
- Company: Established FinTech company revolutionising global money management.
- Benefits: Competitive salary, 25 days holiday, private healthcare, and a learning budget.
- Why this job: Shape the future of AI and machine learning in a dynamic environment.
- Qualifications: Strong skills in Python, SQL, and experience with ML models.
- Other info: Flexible hybrid working and opportunities for real-world impact.
The predicted salary is between 42000 - 84000 £ per year.
We're working with an established FinTech / Payments business that has been helping customers manage and move money globally for many years. The company builds technology-led products that support low-cost, multi-currency payments and money management, operating across several regulated markets.
They're now investing further in their Data Science and AI capability and are looking for a Data Scientist to play a key role in shaping how advanced analytics, machine learning and AI are used across the business.
The role involves turning complex datasets into meaningful insights and production-ready models that influence real business decisions. You'll partner closely with Product, Engineering and Analytics teams, helping to identify where data science and machine learning can add the most value. This role combines hands-on technical work with the opportunity to influence strategy, tooling and ways of working, particularly around AI and ML adoption. You'll be involved across the full lifecycle, from problem definition and experimentation through to deployment, governance and ongoing optimisation.
What you’ll be doing:
- Leading the use of advanced analytics, machine learning and AI within the data team
- Collaborating with Product and Engineering on strategic AI-driven initiatives
- Identifying and developing high-impact use cases for data science and ML
- Helping define ML lifecycle standards, documentation and governance
- Communicating insights and model outputs clearly to technical and non-technical stakeholders
What we’re looking for:
Essential experience:
- Strong grounding in statistical modelling, experimentation and inference
- Advanced Python skills (NumPy, pandas, scikit-learn, PyTorch or TensorFlow)
- Experience building, deploying and optimising ML models in production
- Strong AWS experience (e.g. SageMaker, Lambda or similar services)
- Expert SQL skills and experience working with large, complex datasets
- Solid data engineering fundamentals, including pipelines and APIs
- Comfortable with MLOps practices such as CI/CD, containerisation and monitoring
- Clear, pragmatic communicator who works well across teams
Nice to have:
- Experience with agentic or LLM-based frameworks
- Exposure to causal inference, uplift modelling or advanced experimentation
- Experience working in fintech or another regulated environment
- Awareness of data governance, privacy and model ethics
What’s on offer:
- Competitive salary with flexibility for the right profile
- 25 days holiday plus an additional day off
- Annual learning and development budget
- Private healthcare and wellbeing support
- Pension, life assurance and additional benefits
- Hybrid working with flexibility where possible
This role would suit someone who enjoys working on real-world data problems, wants to influence how AI and machine learning are used responsibly in production, and is looking for a role with both technical depth and business impact.
If you’re interested, apply directly or reach out for a confidential conversation.
Data Scientist in Liverpool employer: Thyme
Contact Detail:
Thyme Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Liverpool
✨Tip Number 1
Network like a pro! Reach out to people in the FinTech space, especially those working as Data Scientists. Use LinkedIn or industry meetups to connect and chat about their experiences. You never know who might have a lead on a job or can give you insider tips!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving machine learning and AI. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the business side of things. Be ready to discuss how your work can impact real business decisions. Practise explaining complex concepts in simple terms – it’s key for communicating with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you. Plus, it’s a great way to ensure your application gets seen by the right people. So, get your CV polished and hit that apply button!
We think you need these skills to ace Data Scientist in Liverpool
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist role. Highlight your advanced Python skills, experience with ML models, and any relevant projects you've worked on. We want to see how you can bring value to our team!
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 your background aligns with our mission at StudySmarter. Don't forget to mention any experience in fintech or regulated environments if you have it!
Showcase Your Projects: If you've worked on any interesting data science projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, we love seeing practical examples of your work and how you approach problem-solving.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Thyme
✨Know Your Data Science Stuff
Make sure you brush up on your statistical modelling and machine learning concepts. Be ready to discuss your experience with Python libraries like NumPy and pandas, as well as any projects where you've built or optimised ML models. This is your chance to show off your technical skills!
✨Showcase Your Collaboration Skills
Since the role involves working closely with Product and Engineering teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight any cross-functional projects you've been part of and how you communicated insights to both technical and non-technical stakeholders.
✨Demonstrate Your Problem-Solving Approach
Think about specific data problems you've tackled before. Be ready to walk through your thought process from problem definition to deployment. This will help interviewers see how you approach challenges and your ability to influence strategy with data-driven insights.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest trends in AI and machine learning, especially within the FinTech space. Being able to discuss current developments or ethical considerations in data governance will show that you're not just technically savvy but also aware of the broader implications of your work.
