Senior Product Portfolio Analyst

This role sits at the intersection of portfolio management, product management and financial/commercial planning, with AI-agentic first ways of working central to the role. You will use AI tools as your default way of working, and prototype and implement reusable agents, data products and automated workflows that remove friction at scale.

You'll report into IFS Product & Technology Strategy & Planning organization, working closely with Product Management leadership. This is an individual-contributor role. Your impact is measured in influence, clarity and adopted capabilities.

You can be located in any of these countries; UK, Netherlands, Poland, Sweden or Sri Lanka

Responsibilities

• Portfolio insight and decision enablement: Turn portfolio data, initiative context and business signals into self-serve insights, decision tools and clear options that help product managers and leaders make better-informed prioritization, investment and sequencing decisions.
• Predictive and scenario-based portfolio analysis: Go beyond reporting on the past: build predictive models that forecast portfolio outcomes, and model alternative scenarios, trade-offs and opportunity costs – a capability we don't have today – so leadership can compare real options instead of relying on gut feel.
• Capital allocation and ROI: Develop clear, evidence-based recommendations for how investment should be allocated across products and define how ROI and benefits realization are tracked once decisions are made.
• Strategy support: Use AI-powered knowledge management to make our strategy and roadmap easier to consume and act on and use portfolio insight to pressure-test it – are we funding the strategy we set out to fund, are we spread too thin, are we over-investing in areas with limited growth potential.
• Root cause analysis: Dig past symptoms to understand why the same friction keeps recurring across teams and help design sustainable solutions rather than local workarounds.
• Turning ambiguity into scalable capability: Clarify ambiguous requirements, translate recurring organizational friction into repeatable processes, operating models and help teams adopt AI-enabled solutions broadly rather than solved repeatedly as one-off problems.
• Agentic enablement: Design, prototype and deploy AI agents, workflows and decision-support tools that scale across the product management organization, replacing repetitive analysis and coordination work with reusable capabilities.
• Enablement over control: Create the tools, data products, AI agents and operating mechanisms that allow product managers to work more independently and effectively, reducing reliance on central coordination while increasing consistency and decision quality.

Qualifications

Essential experience and capabilities

• Background in product operations, portfolio management, product management, or a closely related role, with solid grounding in product planning, roadmapping, prioritisation or portfolio governance.
• Financial and commercial fluency – comfortable modelling portfolio scenarios, trade-offs and opportunity costs, and framing recommendations in terms of ROI and benefits realisation that leadership can act on.
• Comfort operating at the portfolio level – able to turn complex prioritisation and sequencing questions into clear data, evidence and options, so Product Managers and leaders can make confident, well-informed decisions across multiple teams and initiatives.
• Practical confidence using modern AI tools such as Claude, ChatGPT or Copilot to improve analysis, decision-making or ways of working.
• A strong preference for enabling teams through better tools, clearer processes, self-serve answers and AI-enabled ways of working, rather than centralising decisions or becoming a gatekeeper.
• Comfort clarifying ambiguous requirements, shaping a path forward and working with stakeholders to build alignment.

Desirable experience

• 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; you do not need to ship production code, but you understand how the work has changed.
• Experience in enterprise software or B2B SaaS product organisations.
• Familiarity with portfolio management frameworks.
• Exposure to data governance, anonymisation, or data-sharing agreements.

Additional Information

We believe that coming together as a community, in person, is important for innovation, connection and fostering a sense of belonging. Our roles have the right balance of remote and in-office working to enable flexibility for managing your life along with ensuring a real connection with your colleagues and the broader IFS community.