Finance Portfolio Analytics Analyst

Reporting to the Head, Data Science, Analytics, and AI, the Finance Portfolio Analytics Analyst is the hands-on engine behind the analysis that guides R&D portfolio and investment decisions. You will build and maintain the financial and operational models, forecasts and dashboards the team relies on, and support ad hoc strategic analyses — pulling together data from scientific, clinical, financial and operational sources and turning it into clear, accurate outputs.

Key Responsibilities

Analysis & Modelling

• Build, populate and maintain financial and valuation models (e.g. NPV/rNPV, scenario and sensitivity analysis) under guidance.
• Support ad hoc strategic and exploratory analyses; gather, clean and structure data from scientific, clinical, financial and operational sources.
• Help develop and run probabilistic and Monte Carlo simulations and other quantitative analyses.

Portfolio reporting & forecasting

• Maintain portfolio forecasts, metrics, milestones and KPI tracking, and flag variances against plan.
• Build and maintain dashboards, reports and decision materials for review discussions.
• Support improvements to data quality, reporting tools and forecasting methods.

Decision support & collaboration

• Prepare clear, accurate materials for portfolio and product review discussions.
• Synthesise quantitative and qualitative findings into concise summaries, and communicate results clearly to non-technical stakeholders.
• Partner across development, operations, finance and technology teams, taking direction from the Head and senior analytics colleagues and following through on commitments.

Basic Qualifications

• Bachelor’s degree in a quantitative field (engineering, computer science, mathematics, economics, operations research or finance) or life sciences with specific quantitative experience; or equivalent professional experience.
• 2+ years’ experience in financial and operational modelling, data analysis, analytics or forecasting; 2+ years’ experience turning data and analysis into clear, actionable insights and recommendations.
• 2+ years’ experience coding in at least one analytical or programming language (e.g. Python, R or SQL), with exposure to data science app development frameworks (e.g. Shiny, Streamlit or Dash).

Preferred Qualifications

• Experience in pharmaceuticals, biotech, life sciences, consulting or financial services.
• Exposure to drug development or R&D portfolio concepts.
• Strong quantitative fundamentals, with accuracy and attention to detail.
• Ability to communicate analytical results clearly to non-technical stakeholders and to work effectively in cross-functional teams.
• Strong data science fundamentals, with exposure to valuation methods (NPV/rNPV), scenario and sensitivity analysis and Monte Carlo simulation.
• Experience with web app development, from either a data engineering or UI perspective (e.g. Shiny, Streamlit or Dash).
• Interest in or experience with Generative AI tools and frameworks.
• Familiarity with standard software development tools and practices (e.g. Git, CI/CD, containerisation).
• Comfort with ambiguity and managing multiple priorities.

Work Arrangement

This role offers a hybrid working model, with a mix of on-site and remote work. Remote or fully home-working arrangements are not available for this role.