At a Glance
- Tasks: Lead the development of a premium data product that transforms finance processes.
- Company: Join a dynamic global company focused on data innovation in the insurance sector.
- Benefits: Competitive pay, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on career advancement and skill development.
- Why this job: Make a real impact by shaping data strategies that drive business success.
- Qualifications: Experience in data product management and strong analytical skills required.
The predicted salary is between 72000 - 88000 £ per year.
The Data Product Manager (Premium) is a key role within the Global Data Function, accountable for shaping and delivering the Premium data product as part of the Finance Transformation programme. Working closely with the wider product management team, business stakeholders, Technology delivery teams and Architecture, the role will define the product vision, scope and roadmap required to create a trusted, governed and reusable view of premium data. The product will bring together data from multiple business areas and source systems at a consistent level of detail, establish common definitions and quality standards, and enable consistent reporting, analysis and downstream use. The role will lead discovery across the end-to-end data flow—from source systems and interfaces into the Unified Data Ecosystem through to transformation, conformance and consumption—and make clear, evidence-based decisions on priorities, dependencies and phased delivery. It will also matrix-manage the cross-functional delivery team and partner closely with business owners and subject-matter experts to secure adoption, clear ownership and measurable value.
Key Responsibilities
- Product Strategy & Vision: Define and communicate the vision, outcomes and roadmap for the Premium data product, aligned to Finance transformation priorities and wider Group Data strategy.
- Business Discovery & Scope: Lead discovery with Finance, underwriting and business stakeholders to understand current premium and commission processes, reporting needs, pain points and data flows; translate these into a clear, prioritised and phased product scope.
- End-to-End Product Ownership: Own the product across source data, interfaces into the Unified Data Ecosystem, transformation and conformance requirements, and interfaces out to dashboards, analytics and other consuming products e.g. planning tooling.
- Common Data Model: Drive alignment of premium, commission and other data across business areas, including common grain, definitions, dimensions and business rules, while making differences and exclusions explicit.
- Stakeholder & Business Ownership: Establish effective relationships with senior Finance leaders, business product owners, subject-matter experts, Data, Technology and external partners; secure decisions, sign-off and clear accountability for the product.
- Roadmap, Prioritisation & Dependencies: Maintain an integrated roadmap and backlog covering source readiness, interfaces, platform capability, transformation, reporting and adoption; expose trade-offs and manage cross-team dependencies.
- Team Definition & Mobilisation: Define the cross-functional team structure, capabilities, roles and capacity required to deliver the Premium data product once its scope and roadmap are established; identify resource gaps and work with delivery and functional leaders to mobilise the right team for each phase.
- Cross-Functional Delivery Leadership: Matrix-manage engineering, architecture, data quality, analysis, reporting and testing specialists through discovery, design, build, validation and release, while maintaining clear separation between product outcomes and delivery execution.
- Data Governance, Quality & Controls: Define ownership, lineage, metadata, access controls, reconciliation and quality expectations so that premium data is trusted, auditable and suitable for authorised use.
- Adoption & Value Realisation: Define success measures, monitor product health and usage, and work with consumers to embed the product into reporting and decision-making while reducing manual reconciliation and duplicated data preparation.
- Lifecycle & Operating Model: Agree the transition from change to run, including stewardship, support, small-change prioritisation and ongoing product improvement.
Person Specification
- Data Product Leadership: Proven experience defining and managing data products from discovery and strategy through delivery, adoption and ongoing stewardship.
- Commercial & Insurance Acumen: Strong ability to understand how premium data supports financial management, underwriting performance, planning, reporting and executive decision-making.
- Complex Data Landscape: Experience working across multiple source systems, business units and data models to establish common definitions, aligned grain and reusable data structures.
- Stakeholder Leadership: Credibility with senior business, Finance, underwriting, Data and Technology stakeholders, with the ability to facilitate decisions, challenge constructively and build alignment where requirements differ.
- Analytical & Structured Thinking: Ability to break down ambiguous problems, trace business outcomes to source data and transformations, and make pragmatic scope and sequencing decisions.
- Governance & Data Quality: Practical knowledge of data ownership, controls, lineage, reconciliation, access management and quality standards in a regulated environment.
- Delivery Leadership: Experience leading cross-functional teams and managing roadmaps, backlogs, risks and dependencies using Agile and appropriate project disciplines.
- Communication: Excellent written and verbal communication, able to turn complex data and delivery issues into clear choices, recommendations and executive-level updates.
Nice to Have
- Experience in commercial or specialty insurance, particularly premium, underwriting, policy, commission or reinsurance data.
- Understanding of Finance and underwriting reporting, including how premium measures and definitions can vary across business areas and reporting bases.
- Experience delivering enterprise data products on a cloud data platform and enabling Power BI or comparable analytics consumption.
- Experience using Jira, Confluence or similar collaboration and delivery-management tools.
Data Product Manager Insurance in Islington employer: Teksystems
As an Azure Solution Architect with us, you'll thrive in a dynamic work culture that prioritises innovation and collaboration. We offer competitive benefits, including professional development opportunities to enhance your skills in cloud technologies, all while working in a vibrant location that fosters creativity and teamwork. Join us to be part of a forward-thinking company that values your contributions and supports your career growth.
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We think this is how you could land Data Product Manager Insurance in Islington
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We think you need these skills to ace Data Product Manager Insurance in Islington
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Teksystems, 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 Teksystems, 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 Teksystems’s attention and show the tangible impact of your work.
How to prepare for a job interview at Teksystems
✨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 Teksystems.
✨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 Teksystems.
✨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 Teksystems.
