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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 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 Dartford employer: Thyme
Contact Detail:
Thyme Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Dartford
✨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 a lead on that perfect Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and AI. This is your chance to demonstrate how you can turn complex datasets into actionable insights, just like the job requires.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding of statistical modelling. Be ready to discuss your experience with Python, AWS, and SQL, as these are key for the role. Practice explaining your past projects clearly to both technical and non-technical folks.
✨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 seeing candidates who take the initiative to reach out directly. Let’s get you that Data Scientist position!
We think you need these skills to ace Data Scientist in Dartford
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 FinTech background to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our team. Share specific examples of your work with machine learning and analytics to show us what you bring to the table.
Showcase Your Projects: If you've worked on interesting projects or have a portfolio, don’t hesitate to share it! We love seeing real-world applications of your skills, especially those involving complex datasets and AI-driven solutions.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and get back to you quickly!
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 where you’ve influenced decisions using data insights.
✨Communicate Clearly
You’ll need to explain complex data findings to both technical and non-technical stakeholders. Practice simplifying your explanations and think of ways to make your insights relatable. Clear communication can set you apart from other candidates.
✨Understand the Business Context
Familiarise yourself with the FinTech industry and the specific challenges it faces. Think about how data science can drive value in this space and come prepared with ideas on high-impact use cases. Showing that you understand the business will impress your interviewers!
