At a Glance
- Tasks: Lead AI and machine learning projects, transforming complex data into impactful solutions.
- Company: Join Standard Life, a retirement specialist with over 200 years of experience.
- Benefits: Earn up to £75,000, enjoy 38 days leave, private medical cover, and more.
- Other info: Flexible working options available, fostering an inclusive and supportive culture.
- Why this job: Make a real difference in retirement savings while advancing your data science career.
- Qualifications: Extensive experience in data science, strong Python and SQL skills required.
The predicted salary is between 75000 - 75000 £ per year.
Job Type: Perm
Location: 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
Overview: We have an exciting opportunity to join the Pensions & Savings business as a Lead Data Scientist within Strategy and Transformation. Standard Life is a retirement specialist focused entirely on retirement savings and income. We champion the belief that everyone’s journey to and through retirement can be better, and for more than 200 years, we’ve been helping our customers plan and prepare for their financial futures.
The role: 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.
- Act as a technical design authority for data science solutions, ensuring consistency with enterprise architecture, security, risk and compliance expectations.
- Work closely with data engineering, platform and cloud teams to ensure models are scalable, resilient and operationally supported.
- Engage senior stakeholders to:
- Frame business problems effectively.
- Manage expectations and trade‑offs.
- Communicate insight, limitations and outcomes clearly.
- Influence decision‑making using data and evidence.
- Operate comfortably within a complex organisational environment, balancing priorities across multiple teams, initiatives and governance forums.
- Set standards and contribute to the development of data science ways of working, tooling, templates and best practice.
- Provide technical leadership and mentoring to Data Scientists, supporting capability uplift and knowledge sharing across the team.
- Ensure all solutions comply with relevant risk, data governance, model risk and regulatory requirements, maintaining robust evidence and auditability.
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.
We are committed to creating an inclusive culture where everyone feels welcome and supported.
Data Science Lead employer: Standard Life plc
Standard Life is an exceptional employer, offering a dynamic work environment in Edinburgh that prioritises flexibility and employee well-being. With a comprehensive benefits package including up to £75,000 salary, generous annual leave, private medical cover, and opportunities for career growth, we foster a culture of inclusivity and support. As a Lead Data Scientist, you will not only lead impactful AI initiatives but also benefit from a collaborative atmosphere that encourages professional development and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Lead
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, attend meetups, and engage in online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in AI and machine learning. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your end-to-end data science solutions. Include case studies that demonstrate your problem-solving skills and the impact of your work—this will make you stand out during interviews.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. 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 Application:Make sure to customise your CV and cover letter for the Data Science Lead role. Highlight your experience with AI, machine learning, and stakeholder management, as these are key aspects of the job. We want to see how your skills align with what we're looking for!
Showcase Your Technical Skills:Don’t hold back on showcasing your programming skills in Python and SQL. Mention any hands-on experience you have with Azure DevOps and large-scale datasets. We love seeing candidates who can demonstrate their technical depth and delivery focus.
Communicate Clearly:When writing your application, make sure to communicate your insights and experiences clearly. Use straightforward language to explain complex concepts, as this will show us that you can effectively engage with both technical and non-technical stakeholders.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you're genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at Standard Life plc
✨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. This role is all about delivering high-impact AI initiatives, so showcasing your hands-on experience will definitely impress.
✨Understand the Business
Familiarise yourself with Standard Life's mission and the Pensions & Savings sector. Being able to articulate how your data science expertise can directly contribute to improving retirement savings and income for customers will show that you're not just a techie, but someone who understands the bigger picture.
✨Prepare for Stakeholder Engagement
Since this role involves influencing senior stakeholders, practice explaining complex technical concepts in simple terms. Think of examples where you've successfully communicated insights or managed expectations in previous roles. This will demonstrate your ability to bridge the gap between technical and non-technical audiences.
✨Showcase Your Leadership Skills
As a Lead Data Scientist, you'll be expected to mentor others and set standards for the team. Prepare examples of how you've led projects or supported colleagues in their development. Highlighting your coaching experience will show that you're ready to take on a leadership role within the team.
