At a Glance
- Tasks: Lead a team to develop AI-driven analytics solutions and improve decision-making.
- Company: Join a forward-thinking financial services company focused on innovation.
- Benefits: Enjoy flexible working, competitive salary, generous holiday, and wellness support.
- Other info: Embrace a culture of continuous learning and professional development.
- Why this job: Make a real impact by transforming data into actionable insights and driving change.
- Qualifications: Experience in data science, strong leadership skills, and proficiency in Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
This role is available on a part-time, job-share or full-time basis. Location: Flexible – with some travel to our Swindon office where the UK Life team are based. Closing date for applications: 19th June 2026.
The opportunity: As Senior Data Science & Analytics Lead, you will play a pivotal role in evolving our data function from strong management information delivery to a data science‑led, AI‑enabled capability that drives measurable improvements in decision‑making, operational efficiency and risk management. You will be accountable for developing and deploying predictive and statistical models across complex datasets, embedding advanced analytics and AI into core business processes to move from insight generation to automated, data‑driven decisioning. This includes ensuring solutions transition effectively from experimentation into robust, controlled and scalable production use. Combining strong people leadership with technical credibility, this role will build sustainable data science capability within the team, ensuring experimentation, modelling and AI adoption aligned to business priorities and governance expectations. This role is ideal for someone who enjoys turning ambiguity into delivery, balancing people leadership with technical credibility, and innovation leadership – setting direction, coaching others, and acting as a trusted partner to senior stakeholders.
What will you be doing?
- Leadership & Team Management: Lead a team of analysts, supporting performance, development plans, and day‑to‑day prioritisation. Act as a role model for modern analytics practices, curiosity, and outcome‑focused delivery. Build and mature analytical and AI capability within the team, coaching analysts toward more advanced analytics, automation, and AI techniques using learning from apprenticeships and hands‑on delivery.
- Insight & Business Partnership: Partner with senior stakeholders across the UK Life Business and supporting functions to identify opportunities for deeper insight, automation, or improved decision‑making that deliver clear, actionable outcomes. Translate complex business questions into analytical approaches that deliver clear, actionable outputs. Own a prioritised insight and automation development pipeline aligned to business value and capacity. Lead the design and delivery of advanced analytics and data science‑driven solutions, including predictive insight, trend analysis, and decision‑support models. Shape and oversee the responsible use of AI and GenAI to automate insight generation, controls and repeatable MI processes. Act as the accountable lead for exploratory AI and advanced analytics use cases, ensuring appropriate governance, ethics, and risk considerations are met. Guide the transition from pilot and proof‑of‑concept into robust, scalable BAU solutions in partnership with Data Engineering, Governance and Architecture. Embed model lifecycle thinking, including documentation, validation, monitoring, and ongoing performance management where applicable.
- Ways of Working: Embed standards for documentation, validation, and handover into BAU. Champion efficient tooling (e.g. Power BI, Power Platform, SQL, Python) and automation‑first thinking. Promote reuse, simplification, and scalability across the reporting estate. Embed experimentation frameworks (e.g. controlled testing, monitoring, feedback loops) to safely trial and scale advanced analytics and AI‑enabled solutions.
What are we looking for?
- Strong experience applying advanced analytics or data science‑led approaches to ambiguous business problems within Financial Services or similarly regulated environments.
- Proven ability to lead and develop analysts while remaining technically credible.
- Hands‑on experience building and deploying predictive or statistical models in a business environment.
- Strong working knowledge of Python (or equivalent) for data analysis and modelling.
- Experience designing and applying experimentation techniques (e.g. A/B testing, hypothesis testing).
- Advanced skills in SQL and Power BI, including automation of data and MI workflows.
- Experience delivering analytical solutions from prototype into production environments.
- Confident communicator, able to influence stakeholders without relying on hierarchy.
- Experience working within structured delivery practices (e.g. agile/iterative delivery) including backlog and governance management using Azure DevOps or equivalent.
- Experience scaling data science or analytics capability within a team or function.
- Exposure to cloud‑based data platforms or modern data ecosystems (e.g. Snowflake, AWS, Azure).
- Experience applying AI/GenAI techniques in a business context, including automation of insight generation or decisioning.
- Strong understanding of data governance, controls and regulatory considerations within Financial Services.
- Experience working in cross‑functional delivery models with Data Engineering, Architecture and Governance teams.
Qualifications & Learning:
- Degree (or equivalent experience) in a numerate or analytical discipline such as mathematics, statistics, data science, computer science, engineering, or a related field.
- Professional qualifications, certifications, or structured learning in analytics, data science, automation, or AI (e.g. cloud data platforms, analytics engineering, machine learning, or responsible AI) are desirable.
- Commitment to continuous professional development, including keeping pace with emerging analytics, automation, and AI practices, and supporting the learning of others through coaching, apprenticeships, or structured development pathways.
Benefits: We offer a wide range of employee benefits that allow you to tailor your benefits throughout the year. The benefits include:
- 12% defined non‑contributory pension scheme.
- Annual company bonus.
- Private medical insurance.
- Vacation: 28 days holiday a year plus bank holidays, with the option to buy up to an additional 20 days or sell some of your holiday.
- Three days paid volunteering.
- Up to 16 weeks’ full pay for maternity, paternity and adoption leave.
- Access to virtual GP appointments, discounted gym membership, free flu jab and a wealth of wellbeing support.
Our commitment to equality and inclusion: We’re committed to treating all applicants fairly and with respect, irrespective of their actual or assumed background, sexual orientation, disability or any other protected characteristic.
Senior Data Science & Analytics Lead in Swindon employer: Zurich 56 Company Ltd
As a Senior Data Science & Analytics Lead, you will thrive in a dynamic and inclusive work environment that champions innovation and professional growth. With flexible working arrangements and a strong emphasis on employee wellbeing, including generous holiday allowances and a robust pension scheme, our company is dedicated to fostering a culture of collaboration and continuous learning. Join us in Swindon, where you can make a meaningful impact by leading advanced analytics initiatives that drive strategic decision-making and operational excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Science & Analytics Lead in Swindon
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your experience with data science and analytics. We want to see how you tackle real-world problems, so have some examples ready!
✨Tip Number 3
Don’t forget to follow up after interviews! A quick thank-you email can keep you fresh in the interviewer’s mind and show your enthusiasm for the role.
✨Tip Number 4
Apply through our website for the best chance of landing that Senior Data Science & Analytics Lead role. We love seeing candidates who are proactive and engaged with our company!
We think you need these skills to ace Senior Data Science & Analytics Lead in Swindon
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Data Science & Analytics Lead. Highlight your experience with advanced analytics, AI, and team leadership. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how you can drive measurable improvements in decision-making. Keep it engaging and relevant to the job description.
Showcase Your Technical Skills:Don’t forget to mention your hands-on experience with Python, SQL, and Power BI. We’re looking for someone who can hit the ground running, so make sure we see your technical credibility right from the start!
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!
How to prepare for a job interview at Zurich 56 Company Ltd
✨Know Your Data Science Stuff
Make sure you brush up on your advanced analytics and data science techniques. Be ready to discuss your hands-on experience with predictive models, Python, SQL, and any AI techniques you've applied. This role is all about technical credibility, so show them you know your stuff!
✨Showcase Your Leadership Skills
Prepare examples of how you've led teams or mentored analysts in the past. Highlight your ability to balance people management with technical tasks. They want to see that you can inspire others while driving results, so come armed with stories that demonstrate your leadership style.
✨Understand the Business Context
Familiarise yourself with the financial services sector and the specific challenges it faces. Be ready to translate complex business questions into analytical solutions. This shows you can partner effectively with senior stakeholders and deliver actionable insights that align with business priorities.
✨Be Ready for Scenario Questions
Expect to tackle scenario-based questions that assess your problem-solving skills. Think about how you would approach ambiguous situations and turn them into clear, data-driven decisions. Practising these scenarios will help you articulate your thought process during the interview.