About the Role

We are looking for a proactive Data Scientist to support the development of client’s Pipeline Control Tower (PCT) — a central analytics product that provides real-time insights on R&D portfolio performance and project milestone delivery.

The role requires a strong balance of technical skills (SQL, Python, ML/AI, dashboarding) and the ability to interpret and communicate data in a business context. The ideal candidate will work independently, explore behavioral patterns in project management data, and translate them into meaningful KPIs, dashboards, and models.

Requirements 'must have'

• Strong experience with SQL (data wrangling, joins, aggregation).

• Proficiency in Python for analytics and ML (pandas, scikit-learn, etc.).

• Experience building apps/dashboards in Streamlit (or similar frameworks).

• Understanding of ML/AI modelling approaches (classification, regression, clustering).

• Ability to communicate complex findings to non-technical stakeholders.

• Proactive, self-driven, able to work with limited guidance.

• Familiarity with cloud-based environments (Azure, Databricks).

Requirements 'nice to have'

• Pharma R&D / portfolio management experience.

Tasks:

• Analyse project milestone and update logs to identify behavioural patterns of project managers.

• Build and maintain analytics pipelines using SQL and Python.

• Develop interactive dashboards and tools in Streamlit to track KPIs (e.g., on-time delivery).

• Design and prototype ML/AI models (e.g., classification of real vs noise updates, milestone delay prediction).

• Collaborate with business stakeholders to ensure insights are relevant, interpretable, and actionable.

• Work independently, framing problems, defining assumptions, and validating results.