Data, Analytics and AI - Product Manager
Role Overview
The Public Sector Fraud Authority works with departments and public bodies to understand and reduce public-sector fraud.
Its Data Analytics Service provides data analytics services and technology solutions to find and prevent fraud.
The Product Manager delivers data and AI products across their lifecycle to support fraud detection and prevention.
Key Skills for This Role
Full Job Posting
Role overview
The Public Sector Fraud Authority works with departments and public bodies to understand and reduce public-sector fraud.
Its Data Analytics Service provides data analytics services and technology solutions to find and prevent fraud.
The Product Manager delivers data and AI products across their lifecycle to support fraud detection and prevention.
Product management responsibilities
- Develop product vision and strategy for data, analytics, and AI capabilities in line with the Authority's counter-fraud mission.
- Deliver the product roadmap and lead products from discovery through alpha-stage development and beta service implementation.
- Work with multidisciplinary technical teams, including data engineers, data scientists, and business analysts.
- Balance anti-fraud operational needs, user requirements, and technical feasibility using a user-centred, data-informed approach.
- Ensure products deliver measurable outcomes and maximise financial benefits for the public.
Salary and benefits
- Salary is listed as £59,207, with national and London salary ranges provided in the posting.
- The role includes a Civil Service Pension with an employer contribution of 28.97%.
Locations
- The posting lists Glasgow, London, Manchester, Newcastle-upon-Tyne, and York as locations.
Working pattern
- The posting lists flexible working, full-time, and job share working patterns.
About the organisation
The Public Sector Fraud Authority leads government work to tackle fraud against the public sector.
The Cabinet Office describes its values as respect, collaboration, and trust.
Requirements
- Able to balance anti-fraud operational needs, user requirements, and technical feasibility.
- Use a user-centred and data-informed approach to product delivery.
- Work effectively with multidisciplinary technical teams, including data engineers, data scientists, and business analysts.
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