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Finance Portfolio Analytics Manager

GSK

London, GBR

Full-time

Hybrid

Discovered 1 weeks ago

Financial modellingPortfolio analyticsValuation modellingNet present value and risk-adjusted NPVScenario and sensitivity analysisMonte Carlo modelling

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Financial modellingPortfolio analyticsValuation modelling

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Position Summary

The Portfolio Data Science team turns scientific, clinical, operational, and financial inputs into analysis supporting R&D investment decisions.

The Finance Portfolio Analytics Manager builds and leads the analytical capability for R&D portfolio and investment decision-making.

This is a senior individual-contributor role without direct reports, with responsibility for setting standards, guiding analysts, and advising senior stakeholders.

Analytics Capability and Methodology

Design, build, and own valuation models, scenario and sensitivity analysis, probabilistic and Monte Carlo simulation, and portfolio optimisation approaches.
Establish reusable, documented models, templates, and standards that make analyses transparent, reproducible, and auditable.
Improve forecasting methodologies, data quality, and reporting and analytics tooling.

Strategic and Ad Hoc Analysis

Lead analyses addressing complex, ambiguous investment and portfolio questions, including defining problem statements from limited framing.
Develop, evaluate, and stress-test business cases, valuations, and investment scenarios.
Translate scientific, clinical, and operational inputs into quantified financial and investment impact.

Portfolio Performance and Forecasting

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

Decision Support and Governance

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

Collaboration and Enablement

Partner across development, operations, finance, and technology teams to align assumptions, data, and methods.
Set analytical standards, mentor and guide analysts, and champion best practice and responsible use of Generative AI and advanced analytics.

Basic Qualifications

Bachelor's degree in a quantitative field or life sciences with specific quantitative experience.
Experience in financial and operational modelling, valuation, investment analysis, decision science, or a related field.
Experience translating data science insights into actionable recommendations.
Experience defining problems from limited information and managing multiple priorities to agreed timelines.
Experience presenting executive-level analysis and influencing decisions through structured, data-backed recommendations.
Proficiency in at least one analytical or programming language, such as Python or R, with exposure to Shiny, Streamlit, or Dash.

Preferred Qualifications

Advanced degree in finance, a quantitative, scientific, or business discipline.
Exposure to drug development and R&D portfolio or investment decision-making in pharmaceutical, biotech, or a related industry.
Exposure to Monte Carlo modelling, web app development, Generative AI tools, or software development practices such as Git, CI/CD, and containerization.