Finance Portfolio Analytics Manager

GSK

Finance Portfolio Analytics Manager building valuation, forecasting and portfolio analytics for GSK’s global biopharma R&D investments. Guiding senior decisions through data-backed financial insights.

Posted 9/2/2026full-timeLondon • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in financial and operational modeling, investment analysis, and decision science, with a strong ability to translate complex data insights into actionable recommendations. Proficient in analytical programming languages and experienced in developing portfolio analytics toolkits and methodologies.

Highest-signal resume keywords

Financial And Operational ModelingMonte Carlo SimulationPython Or R ProficiencyData Science Insights TranslationInvestment Decision-Making

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NPV/rNPV Valuation ModelsScenario And Sensitivity AnalysisPortfolio OptimizationForecasting MethodologiesValuation And Investment AnalysisKPI TrackingAnalytical Standards SettingBusiness Case DevelopmentMonte Carlo ModellingWeb App Development

Soft Skills

Structured CommunicationInfluencing DecisionsMentoring And Guiding AnalystsProblem DefinitionManaging Multiple Priorities

Tools & Technologies

ShinyStreamlitDashGitCI/CDGenerative AI Tools

Certifications & Qualifications

Bachelor’s Degree In Quantitative FieldAdvanced Degree (MBA, MSc) Preferred

Industry Keywords

PharmaceuticalBiotechR&D PortfolioInvestment GovernanceData QualityAnalytics Tooling

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design, build and own the portfolio analytics toolkit, including NPV/rNPV valuation models, scenario and sensitivity analysis, probabilistic and Monte Carlo simulation, and portfolio optimisation and prioritisation approaches
Establish reusable, documented models, templates and standards that make analyses transparent, reproducible and auditable
Improve forecasting methodologies, data quality, reporting and analytics tooling
Lead ad hoc strategic analyses addressing complex investment and portfolio questions
Define problem statements where 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 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
Partner across development, operations, finance and technology teams to align assumptions, data and methods
Set analytical standards, mentor and guide analysts, and champion responsible use of Gen AI and advanced analytics

Requirements

What you’ll need

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 and operational modelling, valuation, investment analysis, decision science or a related 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 at least one analytical or programming language, such as Python or R
Exposure to data science app development frameworks such as Shiny, Streamlit or Dash
Advanced degree (MBA, MSc or equivalent) in a finance, quantitative, scientific or business discipline (preferred)
Direct exposure to drug development and R&D portfolio or investment decision-making in pharmaceutical, biotech or a related industry (preferred)
Strong data science fundamentals, particularly Monte Carlo modelling (preferred)
Experience with web app development (preferred)
Experience with Generative AI tools and frameworks (preferred)
Experience with standard software development tools and practices, including Git, CI/CD and containerization (preferred)

Benefits

Comp & perks

Hybrid working model with a mix of on-site and remote work
Agile working culture and flexibility opportunities
Equal opportunity employment
Adjustments and support available during the recruitment process