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- Tasks: Lead a team to create impactful AI/ML models and drive innovation.
- Company: Join a well-established, product-led business focused on data-driven solutions.
- Benefits: Enjoy flexible working with one day in the office every two weeks.
- Why this job: Shape the future of machine learning in a collaborative, data-rich environment.
- Qualifications: 6+ years in data science, strong Python and SQL skills required.
- Other info: Opportunity to mentor junior scientists and influence key business decisions.
The predicted salary is between 43200 - 72000 £ per year.
A well-established, product-led business is looking for a Lead Data Scientist to spearhead innovation and drive measurable value through advanced machine learning, experimentation, and the development of production-grade models.
Sitting within a cross-functional data team, this is a hands-on leadership role with the autonomy to shape the modelling roadmap, contribute to R&D strategy, and influence pricing and risk decisions across multiple business lines. You’ll manage a small team of data scientists, guiding them through delivery while remaining actively involved in technical implementation and experimentation.
This is a unique opportunity for someone passionate about building machine learning systems that go beyond prototypes – models that deliver real-world commercial outcomes in a data-rich, regulated environment.
Key Responsibilities- Lead a high-performing team of data scientists to deliver cross-functional, impactful AI/ML initiatives
- Design and implement predictive models and machine learning solutions for core business areas
- Build and productionise models in collaboration with data engineers and platform teams
- Apply advanced statistical techniques to extract insights and guide product and pricing strategies
- Work closely with stakeholders to understand requirements, define modelling goals, and demonstrate business value
- Evaluate vendor data sources, assess economic and technical feasibility, and lead test-and-learn initiatives
- Contribute to the modelling roadmap, experimentation frameworks, and internal data science tooling
- Produce clean, maintainable, version-controlled code and refactor solutions into reusable libraries and APIs
- Coach junior team members and promote best practices across the wider data and analytics community
- Ideally, 6+ years of hands-on experience applying data science techniques in commercial or research-led environments, delivering clear business outcomes
- Advanced academic background (MSc or PhD) in a technical or quantitative field such as Machine Learning, Computer Science, or Statistics
- Strong programming ability in Python (data science ecosystem) and SQL, with proven experience handling large, complex datasets
- Solid track record of building, validating, and deploying machine learning models into real-world systems
- Practical experience designing experiments, selecting evaluation metrics, and applying multivariate testing frameworks
- Leadership mindset – you’ve mentored or managed data science colleagues or helped steer technical decisions in a collaborative team
- Comfortable with version control (Git) and familiar with engineering workflows like CI/CD and containerised environments
- Skilled at working with both structured and unstructured data to unlock insights and power models
- Hands-on experience with Databricks, Apache Spark, or similar tools used in large-scale data processing
- Exposure to machine learning model deployment using APIs or lightweight serving frameworks like Flask or Keras
- Familiarity with geospatial data would be a great bonus!
If this role interests you and you would like to learn more, please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).
Lead Data Scientist employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Make sure to showcase your leadership experience in data science. Highlight any instances where you've mentored or managed a team, as this role requires guiding a small team of data scientists.
✨Tip Number 2
Familiarise yourself with the latest machine learning frameworks and tools mentioned in the job description, such as Databricks and Apache Spark. Being able to discuss your hands-on experience with these tools can set you apart during interviews.
✨Tip Number 3
Prepare to discuss specific projects where you've built and deployed machine learning models. Be ready to explain the business outcomes of these projects, as demonstrating real-world impact is crucial for this role.
✨Tip Number 4
Network with professionals in the data science community, especially those who have experience in regulated environments. This can provide insights into industry best practices and may even lead to referrals for the position.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly focusing on machine learning and leadership roles. Use specific examples of projects where you've delivered measurable outcomes.
Craft a Compelling Cover Letter: In your cover letter, express your passion for building machine learning systems that deliver real-world results. Mention your experience with advanced statistical techniques and how you can contribute to the company's goals.
Showcase Technical Skills: Clearly outline your programming skills in Python and SQL, as well as your experience with tools like Databricks or Apache Spark. Provide examples of how you've handled large datasets and deployed machine learning models.
Highlight Leadership Experience: Discuss any previous experience mentoring or managing data science teams. Emphasise your ability to guide team members and promote best practices within a collaborative environment.
How to prepare for a job interview at Xcede
✨Showcase Your Technical Skills
As a Lead Data Scientist, you'll need to demonstrate your expertise in Python and SQL. Be prepared to discuss specific projects where you've built and deployed machine learning models, and don't hesitate to share code snippets or examples of your work.
✨Highlight Leadership Experience
This role involves managing a team, so it's crucial to showcase your leadership skills. Share experiences where you've mentored junior data scientists or led cross-functional teams, emphasising how you guided them through technical challenges.
✨Discuss Business Impact
Employers want to see how your work translates into business outcomes. Prepare to discuss how your data science initiatives have driven measurable value in previous roles, particularly in terms of product development or pricing strategies.
✨Prepare for Technical Questions
Expect to face technical questions related to machine learning techniques, statistical methods, and model evaluation metrics. Brush up on your knowledge of multivariate testing frameworks and be ready to explain your thought process in designing experiments.
