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For Companies At a Glance
- Tasks: Transform complex data into insights and models that drive business decisions.
- Company: Established FinTech leader 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 statistical modelling, Python skills, and experience with ML models.
- Other info: Flexible hybrid working and excellent career growth opportunities.
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 Wakefield employer: Thyme
Contact Detail:
Thyme Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Wakefield
✨Tip Number 1
Network like a pro! Reach out to people in the FinTech space, especially those working with data science. Use platforms like LinkedIn to connect and engage with them. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving machine learning and AI. This will give potential employers a taste of what you can do and how you can add value to their team.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science. Be ready to discuss your experience with Python, SQL, and AWS, as well as how you've tackled real-world data problems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to make an impact in the world of data science.
We think you need these skills to ace Data Scientist in Wakefield
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with statistical modelling, Python, and ML models. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include any relevant projects or case studies that demonstrate your ability to turn complex datasets into insights. This is your chance to show us your hands-on experience with data science and AI!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to communicate your experience and how you can add value to our team. Remember, we appreciate a pragmatic communicator!
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Thyme
✨Know Your Data Science Fundamentals
Make sure you brush up on your statistical modelling and machine learning concepts. Be ready to discuss how you've applied these in real-world scenarios, especially in relation to the FinTech sector. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Technical Skills
Prepare to demonstrate your advanced Python skills and experience with libraries like NumPy and pandas. You might be asked to solve a problem on the spot, so practice coding challenges beforehand. Also, be ready to discuss your experience with AWS services and how you've deployed ML models in production.
✨Communicate Clearly
As a Data Scientist, you'll need to convey complex insights to both technical and non-technical stakeholders. Practice explaining your past projects in simple terms, focusing on the impact of your work. This will highlight your ability to bridge the gap between data science and business strategy.
✨Prepare for Collaboration Questions
Since this role involves working closely with Product and Engineering teams, think about examples from your past where you've successfully collaborated across departments. Be ready to discuss how you identified high-impact use cases and contributed to strategic initiatives, particularly around AI and ML.
