We are looking for a proactive Data Scientist to support the development of a Pipeline Control Tower (PCT) — a central analytics product providing real-time insights into portfolio performance and project milestone delivery.

This role requires a mix of strong technical expertise (SQL, Python, ML/AI, dashboarding) and business acumen to interpret data in a meaningful way. You’ll work independently, analysing behavioural patterns in project management data and translating them into KPIs, dashboards, and predictive models that drive data-informed decisions.

Key Responsibilities

• Analyse project milestones 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 key performance indicators (e.g., on-time delivery).
• Design and prototype ML/AI models, such as classification of real vs. noise updates and milestone delay prediction.
• Collaborate with business stakeholders to ensure insights are relevant, interpretable, and actionable.
• Work independently, framing problems, defining assumptions, and validating results.

Requirements (Must Have)

• Strong experience with SQL (data wrangling, joins, aggregations).
• Proficiency in Python for analytics and ML (pandas, scikit-learn, etc.).
• Hands-on experience with Streamlit (or similar frameworks) for dashboarding.
• Solid understanding of ML/AI modelling approaches (classification, regression, clustering).
• Excellent English communication skills (5/5) — able to explain complex insights to non-technical stakeholders.
• Highly proactive, self-driven, and comfortable working with limited guidance (absolutely crucial).
• Familiarity with cloud-based environments (Azure, Databricks) is a plus.