Product Manager, AI Transformation Job IDinsight
IT Jobs. IDinsight Jobs
The Product Manager will own IDinsight’s internal roadmap for accelerating and disrupting our work by leveraging AI, while contributing to external advisory engagements that help our partners do the same. The Product Manager will scope, build, and deploy AI-powered products that change how IDinsight and our partners deliver our core services. The role blends product management, user research, and technical coordination to ensure we’re building the right things, shipping them fast, and generating real impact.
Key Responsibilities
As a Product Manager on the AI Transformation team, the day-to-day work may include:
- Conducting user research with internal and external teams to understand workflows and pain points, and prioritizing where AI can deliver step-change improvements.
- Defining problem statements and translating user needs into actionable product specifications.
- Working with data scientists and engineers to scope, build, and deploy bespoke tools, applying agile principles to ship fast and kill what doesn’t work.
- Scoping the product and technical components of external AI advisory engagements, including contributing to proposals and coordinating delivery.
- Tracking efficiency gains from deployed tools with hard metrics like hours saved, tasks automated, cycle time reductions and iterating based on usage data and feedback.
- Creating playbooks and documentation that other teams can replicate.
- Synthesising, visualizing, and communicating results: Dashboards, plots, interactive viz, presentations and reports.
Required Technical Qualifications
- A bachelor’s degree in a quantitative or technical field such as Engineering, Computer Science, Applied Math, or Data Science.
Minimum 5 years of relevant professional experience, including at least 3 years in a Product Manager, Technical PM, or product-oriented consulting role focused on digital products or AI/data solutions. - Strong working knowledge of advanced data science and AI concepts relevant to DSEM products (e.g., LLMs, GenAI applications, ML algorithms), and the ability to translate technical capabilities to non-technical stakeholders.
- Expert command of product analytics, growth experimentation (A/B testing), and proficiency in leveraging data platforms and pipeline concepts (e.g., SQL, Python) to define and track complex growth metrics.
- Experience conducting user research, translating fuzzy problems into clear solutions, defining problem statements, and validating assumptions through interviews and data.
- Proficiency in applying agile principles to manage product development like sprint planning, backlog prioritization, retrospectives, and stakeholder communication.
- Well-versed with technical architecture, such as cloud platforms (AWS/GCP), data integration workflows, or deployment constraints, in order to credibly engage partners and funders.
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