Description
At GSK, we unite science, technology and talent to get ahead of disease together. The Portfolio Data Science team turns scientific, clinical, operational and financial inputs into analysis and insight that guide investment decisions across short-, medium- and long-range horizons.
As a Finance Portfolio Analytics Analyst, you will be the hands-on engine behind the analysis that guides R&D portfolio and investment decisions. You will build and maintain financial and operational models, forecasts and dashboards, and support ad hoc strategic analyses.
Key Responsibilities:
- 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.
- 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.
- 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.