Finance Portfolio Analytics Manager

Position Summary

Reporting to the Head, Data Science, Analytics, and AI, the Finance Portfolio Analytics Manager builds and leads the analytical capability that underpins R&D portfolio and investment decision-making. You will design the models, frameworks and dashboards the team relies on, and lead ad hoc strategic analyses that answer complex, high-stakes portfolio questions, translating scientific and clinical information into quantified investment and financial impact.

• Design, build and own the portfolio analytics toolkit, valuation models (NPV/rNPV), scenario and sensitivity analysis, probabilistic and Monte Carlo simulation, and portfolio optimisation and prioritisation approaches.
• Establish reusable, well-documented models, templates and standards so that analyses are transparent, reproducible and auditable.
• Continuously improve forecasting methodologies, data quality, and reporting and analytics tooling.

• Lead ad hoc strategic analyses to address complex, ambiguous investment and portfolio questions, defining the problem statement where only limited framing exists.
• Develop, evaluate and stress-test business cases, valuations and investment scenarios.
• Translate scientific, clinical and operational inputs into quantified financial and investment impact.

• Build and maintain portfolio forecasts across annual, multi-year and long-range planning horizons.
• Define and track portfolio metrics, milestones and KPIs; monitor performance against plan and surface variances and risks with recommended actions.
• Support investment allocation and budget phasing aligned to portfolio priorities.

• Prepare insights, materials and recommendations for portfolio and product review discussions and investment governance cycles.
• Present trade-offs, risks and financial impact to senior leadership, and influence decisions through structured, data-backed recommendations.
• Consolidate inputs from scientific, clinical, regulatory, commercial, finance and technology stakeholders into a coherent portfolio view.

• Partner across development, operations, finance and technology teams to align on assumptions, data and methods.
• Set analytical standards and mentor and guide analysts; champion best practice and the responsible use of Gen AI and advanced analytics to accelerate and strengthen analysis.

• Bachelor’s degree in a quantitative field (engineering, computer science, mathematics, economics, operations research, finance ) or life sciences with specific quantitative experience.
• Demonstrated experience in financial & operational modelling, valuation, investment analysis, decision science or a related area field.
• Demonstrated expertise translating data science insights into actionable recommendations.
• Experience defining problem statements from limited initial information and managing multiple parallel priorities to agreed timelines.
• Experience preparing and presenting executive-level analysis and influencing decisions through structured communication and data-backed recommendations.
• Proficiency with least one analytical or programming language (e.g. Python or R), together with exposure to data science app development frameworks (Shiny, Streamlit, Dash etc.)

• Advanced degree (MBA, MSc or equivalent) in a finance, quantitative, scientific or business discipline.
• Direct exposure to drug development and R&D portfolio or investment decision-making in pharmaceutical, biotech or a related industry.
• Strong data science fundamentals with particular exposure to Monte Carlo modelling
• Experience with web app development either from a data…