Senior Product Portfolio Analyst
HybridColombo, Western Province, Sri Lanka
Job Summary
Turn portfolio data and business signals into self-serve insights and decision tools that enable product leaders to prioritize investments and sequence initiatives effectively. Build predictive models and scenario-based analyses to forecast outcomes, model trade-offs, and provide evidence-based recommendations for capital allocation and ROI tracking. Design, prototype, and deploy AI agents, workflows, and automated decision-support tools to replace repetitive coordination work and scale reusable capabilities across the product organization. Clarify ambiguous requirements, identify root causes of recurring friction, and translate organizational challenges into repeatable operating models and adopted ways of working. This individual-contributor role sits at the intersection of portfolio management, product strategy, and financial planning, reporting to IFS Product & Technology Strategy & Planning leadership. Candidates must combine strong portfolio thinking with analytical judgment and the ability to leverage modern AI tools like Claude or Copilot to drive adoption. Located in the UK, Netherlands, Poland, Sweden, or Sri Lanka, this position supports IFS's global mission to solve society's greatest challenges through agile, AI-driven enterprise software.
Required Qualifications
- Background in product operations, portfolio management, product management, or a closely related role
- solid grounding in product planning, roadmapping, prioritisation or portfolio governance
- Financial and commercial fluency
- Comfort operating at the portfolio level
- Practical confidence using modern AI tools such as Claude, ChatGPT or Copilot
- A strong preference for enabling teams through better tools, clearer processes, self-serve answers and AI-enabled ways of working
- Comfort clarifying ambiguous requirements, shaping a path forward and working with stakeholders to build alignment
Desired Qualifications
- Hands-on experience building or configuring AI agents, workflows or self-service tools, for example via Claude, MCP-style tool integrations, Copilot or low-code agent platforms
- Enough understanding of how software gets built in an AI-assisted world to partner credibly with engineering
- Experience in enterprise software or B2B SaaS product organisations
- Familiarity with portfolio management frameworks
- Exposure to data governance, anonymisation, or data-sharing agreements
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