Define and own the product vision, strategy, and roadmap for the AI, Analytics & Data Science product portfolio.
Conduct continuous market and competitor analysis to identify new opportunities and ensure product differentiation.
Prioritise the product backlog based on business impact, client feedback, and technical feasibility.
Make clear build, buy, or partner decisions for new capabilities.
**Product Discovery & Definition:**
Lead product discovery by engaging directly with clients, sales, and account managers to understand user needs and pain points.
Translate complex user needs and business requirements into clear, concise user stories and technical specifications for the data science and engineering teams.
Act as the "voice of the customer" and key stakeholder, managing the product backlog and leading sprint planning.
**Go-to-Market & Commercialisation:**
Develop and execute the complete go-to-market strategy for all new AI products and features.
Create and maintain a library of high-impact sales enablement materials, including case studies, ROI models, and competitor battle cards.
Partner with marketing to create compelling product messaging that translates technical AI capabilities into clear business value.
**Cross-Functional Leadership & Adoption:**
Lead a cross-functional team of data scientists, engineers, designers, and commercial stakeholders, fostering a collaborative and high-performance culture.
Integrate AI products into the core client onboarding process, tracking and analysing adoption rates to drive deeper engagement.
Regularly present the product roadmap, performance data, and success stories to leadership and the wider company.
Requirements
**Skills & Qualifications:**
**Experience:** 3-5+ years of experience in Product Management or Product Ownership, ideally within a B2B SaaS, iGaming, or tech company.
**Domain Knowledge:** Demonstrable experience working with technical products, data, or AI/ML. You must be comfortable having in-depth discussions with data scientists and engineers.
**Technical Skills:** Strong analytical skills are required. Proficiency in SQL for data querying is a significant plus.
**Communication:** Proven ability to translate complex technical concepts into simple, compelling business terms for a non-technical audience.
**Methodology:** Experience with agile/scrum methodologies, managing backlogs, and writing effective user stories is essential.
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