Product Manager, AI Transformation at IDinsight
IDinsight View all jobs
- Nairobi
- Permanent
- Full-time
- 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.
- 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.
- A bachelor’s degree in a quantitative or technical field such as Engineering, Computer Science, Applied Math, or Data Science.
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