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- Tasks: Lead AI and machine learning projects, transforming complex data into impactful solutions.
- Company: Join a leading Pensions & Savings business in Edinburgh with a focus on innovation.
- Benefits: Earn up to £75,000, enjoy 38 days leave, private medical cover, and flexible working options.
- Other info: Flexible working arrangements and opportunities for career growth and mentoring.
- Why this job: Make a real difference by driving advanced analytics and AI initiatives in a dynamic environment.
- Qualifications: Extensive experience in data science, strong Python and SQL skills, and stakeholder management expertise.
The predicted salary is between 75000 - 75000 £ per year.
Job Type: Perm
Location: This role will be based in our Edinburgh office.
Flexible working: All of our roles are open to part-time, job-share and other types of flexibility. We will discuss what is important to you and balancing this with business requirements during the recruitment process.
Salary and benefits: Up to £75,000 plus discretionary bonus, private medical cover, 38 days annual leave, excellent pension, 12x salary life assurance, career breaks, income protection, 3x volunteering days and much more.
Closing Date: 13th May
We have an exciting opportunity to join the Pensions & Savings business as a Lead Data Scientist within Strategy and Transformation. As a Lead Data Scientist, you will take technical and delivery ownership for complex, high-impact AI, machine learning and analytic initiatives across the business. You will lead the end-to-end design, development, deployment and ongoing optimisation of advanced analytics and ML solutions, ensuring they deliver measurable business outcomes and meet regulatory, risk and governance standards.
You will act as a senior technical authority and delivery lead, working closely with stakeholders across product, operations, technology, risk and transformation. You will play a key role in establishing modern data science and MLOps practices, enabling the team to scale analytics and AI safely, reliably and at pace. This is a hands-on role that requires strong technical depth, delivery focus, and the ability to navigate complex organisational structures, influence senior stakeholders, and translate business problems into production-grade AI solutions.
Key responsibilities
- Lead the end-to-end delivery of AI / ML and analytic initiatives, from problem definition and solution design through to deployment, monitoring and continuous improvement.
- Design and build production-grade machine learning solutions, applying appropriate modelling techniques (supervised, unsupervised, NLP, optimisation) aligned to business needs.
- Champion and apply MLOps best practice, including:
- Model versioning, testing and validation
- CI/CD pipelines using Azure DevOps
- Automated deployment, monitoring, drift detection and retraining
- Documentation, audit trails and governance artefacts
- Frame business problems effectively
- Manage expectations and trade-offs
- Communicate insight, limitations and outcomes clearly
- Influence decision-making using data and evidence
What We’re Looking For
Essential experience
- Extensive experience delivering end-to-end data science / machine learning solutions in a production environment.
- Strong programming skills in Python and SQL, with experience working with large-scale datasets (e.g. Spark, distributed compute).
- Hands-on experience with Azure DevOps (or equivalent) for source control, pipelines and deployment automation.
- Solid software engineering discipline, including Git-based workflows and code reviews.
- Modular, testable code.
- Experience working with cloud-based data platforms (data lakes, warehouses) and partnering closely with data engineering teams.
- Strong stakeholder management skills, with the ability to explain complex technical concepts to non-technical audiences and influence senior decision-makers.
Desirable experience
- Experience operating in highly regulated environments (e.g. financial services).
- Proven experience implementing MLOps practices, including model lifecycle management, CI/CD and monitoring.
- Familiarity with model governance, validation and audit requirements.
- Experience contributing to enterprise-wide analytics or AI platforms.
- Coaching or technical leadership experience within data science teams.
Data Science Lead employer: Standard Life (previously Phoenix Group)
Contact Detail:
Standard Life (previously Phoenix Group) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Lead
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews by practising common data science questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and technical skills.
✨Tip Number 3
Showcase your projects! Whether it's through a portfolio or GitHub, having tangible examples of your work can really set you apart. Make sure to highlight any AI or ML solutions you've developed that align with the role.
✨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 proactive about their job search!
We think you need these skills to ace Data Science Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Science Lead role. Highlight your experience with AI, machine learning, and any relevant projects you've led. We want to see how your skills align with what we're looking for!
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 you can contribute to our team. Don't forget to mention your experience with stakeholder management and MLOps practices.
Showcase Your Technical Skills: Since this role requires strong programming skills in Python and SQL, make sure to highlight your technical expertise. Include specific examples of projects where you've used these skills to deliver impactful solutions.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Standard Life (previously Phoenix Group)
✨Know Your Stuff
Make sure you brush up on your technical skills, especially in Python and SQL. Be ready to discuss your experience with machine learning solutions and how you've applied them in real-world scenarios. Prepare examples that showcase your ability to lead projects and deliver results.
✨Understand the Business
Familiarise yourself with the company's goals and how data science fits into their strategy. Be prepared to discuss how you can translate complex business problems into actionable AI solutions. This shows that you’re not just a techie but also understand the bigger picture.
✨Engage with Stakeholders
Practice explaining technical concepts in simple terms. You’ll need to influence senior stakeholders, so think about how you can communicate insights and manage expectations effectively. Role-play these conversations with a friend to build confidence.
✨Showcase Your Leadership Skills
As a Lead Data Scientist, you'll be expected to mentor others. Prepare to discuss your coaching experiences and how you've uplifted team capabilities in the past. Highlight any frameworks or best practices you've implemented to improve team performance.