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For Companies At a Glance
- Tasks: Design and deliver innovative data products for the insurance industry.
- Company: Accelerant, a leading data-driven risk exchange in specialty insurance.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of insurance data products.
- Qualifications: 6-10 years in data roles with strong communication and analytical skills.
- Other info: Collaborative environment with a focus on innovation and impact.
The predicted salary is between 36000 - 60000 ÂŁ per year.
About Accelerant
Accelerant is a data-driven risk exchange connecting underwriters of specialty insurance risk with risk capital providers. Founded in 2018 by a group of longtime insurance industry executives and technology experts, Accelerant aims to rebuild the way risk is exchanged for better outcomes. The Accelerant risk exchange operates across more than 20 countries and 250 specialty products, with insurers awarded an AM Best A- (Excellent) rating.
Role Overview
The Data Product Analyst is a core contributor within a data mesh operating model, embedded in or closely aligned to business domains and accountable for the design, delivery, and evolution of insurance domain data products. This role will prioritise data products that enable improvements across Reserving, Reinsurance, and the Month Close process, including definition alignment, embedded reconciliation controls, and audit-ready lineage and documentation.
As a domain “design authority,” the Data Product Analyst ensures data products are semantically correct, analytically fit for purpose, interoperable across domains, and compliant with relevant regulatory and reporting requirements.
Experience
Typically 6–10 years in data-aligned roles (e.g., data product, BI/analytics engineering, data governance/stewardship, domain analytics, technical BA/PO).
Key Responsibilities
- Data Product Definition & Design: Translate domain needs across underwriting, pricing, claims, finance, and distribution into data product specifications with clear scope, assumptions, and acceptance criteria. Define and maintain core insurance entities and relationships, including grain and aggregation rules. Define standard insurance metrics and logic and ensure consistent interpretation across consuming teams. Ensure the data product model accurately represents complex structures.
- Delivery & Lifecycle Management: Design, enhance, and maintain data products in collaboration with data engineering and platform teams. Oversee the full data product lifecycle, including versioning, enhancements, deprecation, and backward compatibility. Support domain prioritisation and roadmap planning for data products.
- Federated Governance, Cataloging & Quality: Define and maintain documentation to ensure certified data products are shipped with appropriate metadata. Collaborate with Data Quality and Data Governance teams to apply federated standards while preserving domain ownership. Define and execute validation and testing strategies to ensure reliability for analytics and reporting consumers.
- Change Management, Consumer Enablement & Adoption: Perform impact analysis and coordinate change management for schema/metric/logic changes across consuming domains. Act as the primary point of contact for data product consumers, supporting adoption and correct usage.
Required Outputs / Artifacts
- Data Product Specification: scope, entities, grain, metrics, assumptions, transformation/derivation logic
- Data Product Contract: schema, SLAs, quality thresholds, lineage expectations, compatibility/versioning rules
- Release Readiness Note: consumer communication, backward compatibility, cutover plan, monitoring expectations
Skills & Behaviours
- Strong structured communication: concise, decision-oriented, able to drive alignment across Finance/Actuarial/Operations.
- Ability to manage ambiguity, converge on definitions, and prevent “definition drift”.
- Working knowledge of modern data platforms and concepts.
- Practical governance-by-design mindset.
Domain Knowledge (Strongly Preferred)
- Strong insurance domain knowledge covering policies/claims/premiums and downstream reporting usage.
- Experience with Reserving, Reinsurance, and/or Finance Month Close data and reporting processes is strongly preferred.
Data Product Analyst in London employer: Accelerant
Contact Detail:
Accelerant Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Product Analyst in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect 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 interviews by researching the company and its products. Understand their data products and how they fit into the insurance landscape. This will help you stand out and show that you're genuinely interested in the role.
✨Tip Number 3
Practice your communication skills! As a Data Product Analyst, you'll need to convey complex ideas clearly. Try mock interviews with friends or use online platforms to refine your pitch and responses.
✨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, it shows you're serious about joining the team at Accelerant.
We think you need these skills to ace Data Product Analyst in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Product Analyst role. Highlight your experience in data product design and your understanding of insurance domain knowledge. We want to see how your skills align with what we’re looking for!
Showcase Your Communication Skills: Since strong structured communication is key for this role, don’t shy away from demonstrating this in your application. Use clear and concise language, and make sure your points are well-organised. We love a good, easy-to-read application!
Highlight Relevant Experience: Be sure to emphasise your past roles that relate to data governance, analytics, or product management. If you’ve worked on projects involving Reserving or Reinsurance, let us know! We’re keen to see how your background fits into our needs.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details directly and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Accelerant
✨Know Your Data Inside Out
As a Data Product Analyst, you’ll need to demonstrate a solid understanding of data products and their lifecycle. Brush up on key insurance metrics and concepts like reserving and reinsurance. Be ready to discuss how you’ve previously translated domain needs into actionable data specifications.
✨Showcase Your Communication Skills
Strong structured communication is crucial for this role. Prepare to articulate your thoughts clearly and concisely during the interview. Think about examples where you’ve successfully driven alignment across different teams, especially in finance or operations.
✨Prepare for Scenario-Based Questions
Expect questions that assess your ability to manage ambiguity and prevent definition drift. Practice responding to hypothetical scenarios where you might need to converge on definitions or handle changes in data products. This will showcase your problem-solving skills and adaptability.
✨Familiarise Yourself with Governance Practices
Since governance-by-design is a key aspect of the role, be prepared to discuss how you’ve embedded quality thresholds and metadata into your previous projects. Highlight any experience you have with data quality and governance frameworks, as this will resonate well with the interviewers.