At a Glance
- Tasks: Lead the development of innovative data products that drive better decision-making.
- Company: Join WTW, a forward-thinking company focused on data-driven solutions.
- Benefits: Enjoy 25 days annual leave, private healthcare, and a pension scheme with matched contributions.
- Other info: Hybrid working model with opportunities for professional growth and community involvement.
- Why this job: Make a real impact by turning complex problems into actionable data solutions.
- Qualifications: Experience in data products, strong analytical skills, and proficiency in SQL or Python.
The predicted salary is between 45000 - 55000 £ per year.
Description
WTW’s Risk & Broking data function is building data products that help colleagues make better, faster, and more consistent decisions.
Operating as part of the central data function, the team works with a broad engineering capability, domain specialists, regional data colleagues, and business stakeholders to create products for Great Britain and the global business.
We are looking for a hands-on Senior Data Product Manager who can turn ambiguous business problems into viable data-product opportunities.
You will combine product judgement, analytical problem-solving, and technical prototyping to test ideas quickly, establish value, and lead selected products through development, launch, and ongoing improvement.
This is an individual-contributor role for someone comfortable moving between business problems, data, technology, and product delivery.
You will not simply write requirements for others.
You will explore data, build working prototypes, challenge assumptions, and create the evidence needed to determine whether and how a product should be scaled.
This is a 12-month FTC opportunity, based in London, with a hybrid working arrangement requiring 2 days in the office per week.
The standard working week is 35 hours.
The Role
- Product discovery and problem definition
- Work with business stakeholders and domain specialists to understand decisions, workflows, pain points, and opportunities that could be addressed through data products.
- Convert broad or ambiguous challenges into clear problem statements, target users, desired outcomes, hypotheses, and measurable product objectives.
- Assess product opportunities based on business value, user need, data readiness, technical feasibility, scalability, and alignment with the broader data-product portfolio.
- Identify when a request should become a reusable product and when a simpler analytical or process solution is more appropriate.
- Prototyping and feasibility
- Personally build working proofs of concept using tools such as SQL, Python, Databricks, Power BI, AI tooling, and appropriate low-code platforms.
- Explore and profile data to understand quality, coverage, structure, limitations, and suitability for the intended use case.
- Use prototypes to test product concepts with users, expose assumptions, and generate evidence before significant engineering investment.
- Work with data engineers, architects, analysts, and platform specialists to determine how successful prototypes should be industrialised.
- Ensure prototype work is appropriately transitioned into maintainable, governed, and scalable solutions rather than becoming unsupported production tooling.
- Product ownership and delivery
- Own selected data products from discovery through prototype, development, launch, adoption, and improvement.
- Define product vision, outcomes, scope, roadmap, success measures, and priorities.
- Translate user and business needs into clearly articulated product requirements, data requirements, and acceptance criteria.
- Make day-to-day prioritisation and scope decisions within the agreed product strategy.
- Balance speed of experimentation with data quality, architecture, governance, security, and maintainability.
- Partner closely with engineering while retaining clear accountability for the problem, user outcome, and product value.
- Stakeholder collaboration
- Build effective relationships with business stakeholders, domain specialists, engineers, architects, analysts, and regional data colleagues.
- Facilitate structured product conversations that distinguish real user needs from proposed solutions.
- Explain technical concepts and analytical findings clearly to non-technical stakeholders.
- Create transparency around assumptions, dependencies, risks, product choices, and expected outcomes.
- Help establish consistent data-product practices across the central function.
- Product performance and improvement
- Define and monitor measures covering product use, user outcomes, data quality, operational efficiency, and business benefit.
- Use feedback and product evidence to improve, scale, reposition, or stop products.
- Ensure product documentation, ownership, lineage, intended use, and limitations are clear.
- Contribute reusable methods, templates, prototypes, and lessons to the wider data-product capability.
Qualifications
What you’ll bring
- Proven experience across data, analytics, technology, or digital products, with a strong track record of owning and delivering data-enabled products or solutions.
- Strong evidence of solving ambiguous business problems and converting them into practical, evidence-based solutions.
- Hands-on ability to interrogate data and build working prototypes using several of SQL, Python, Databricks, Power BI, AI tooling, or low-code tools.
- Experience undertaking product discovery, defining user needs, setting product outcomes, prioritising work, and collaborating with engineering teams.
- Ability to assess data quality and technical feasibility without relying entirely on others to interpret the underlying data.
- Experience taking at least some products or analytical solutions beyond ideation into sustained use.
- Strong written and verbal communication skills with business, domain, data, and technology stakeholders.
- Ability to work independently while building alignment across a complex organisation.
Desirable experience
- Commercial insurance, insurance broking, specialty insurance, claims, placement, portfolio analytics, or underwriting experience.
- Experience with data mesh, domain-oriented data products, common data models, data contracts, metadata, and data governance.
- Experience industrialising analytical prototypes with data-engineering and architecture teams.
- Experience integrating generative AI or machine learning into business products.
- Familiarity with regulated environments and the responsible use of commercially sensitive data.
What we offer
Enjoy a benefits package designed to help you thrive, both professionally and personally.
You'll receive 25 days of annual leave plus an extra WTW day to relax and recharge.
Our comprehensive health and wellbeing offering includes private healthcare, life insurance, group income protection, and regular health assessments, all giving you peace of mind.
Secure your future with our defined contribution pension scheme, featuring matched contributions up to 10% from the company.
We support your growth and balance with hybrid working options, access to an employee assistance programme, and a fully paid volunteer day to make a difference in your community.
On top of these, you can opt into a variety of additional perks including an electric vehicle car scheme, share scheme, cycle-to-work programme, dental and optical cover, critical illness protection, and much more.
Start making the most of your career and wellbeing with a range of benefits tailored for you.
Equal Opportunity Employer
We’re committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants.
If you foresee any barriers, from the application process through to joining WTW, please email
Senior Data Product Manager - 12 months FTC in London employer: WTW group
WTW group offers a dynamic work environment that fosters collaboration and innovation, as seen in roles like the Global Marine Marketing Lead, which emphasizes teamwork and strategic engagement. The company provides opportunities for professional growth through hands-on experiences, such as internships and graduate programs in Insurance Technology, allowing employees to develop practical skills in a supportive setting. Additionally, WTW group is committed to maintaining high standards of service and governance, ensuring a stable and rewarding workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Product Manager - 12 months FTC in London
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We think you need these skills to ace Senior Data Product Manager - 12 months FTC in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at WTW group, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to WTW group, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab WTW group’s attention and show the tangible impact of your work.
How to prepare for a job interview at WTW group
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at WTW group.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at WTW group.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at WTW group.
