Overview
The incumbent supports data analysis and reporting by applying established analytical methods and tools to translate defined information needs into routine analyses, produce standard visualizations, and maintain documented data products. The role contributes to good data management practices and knowledge sharing.
Key Responsibilities
- Acquire, clean, validate and join data from structured and unstructured sources.
- Build feature stores; implement data quality checks.
- Enforce FAIR data principles; comply with data protection, anonymization/pseudonymization, and data sharing agreements.
- Support the development of predictive, classification, segmentation, recommendation, forecasting, and optimization models using machine learning and AI techniques.
- Contribute to the design and implementation of retrieval-augmented generation (RAG) pipelines, prompt engineering, guardrails, and evaluation methods for generative AI applications.
- Support and guide the design, implementation and use of Excel or SQL based tools.
- Support maintenance of current data consolidation process flow.
- Produce data reports, analyses and insights.
- Create and maintain up-to-date dashboards and reporting tools.
- Deliver training materials and enablement sessions for end users.
- Run brown bags on topics like feature stores, prompt engineering, causal inference, experiment design.
- Perform other tasks as requested to support the MSC team.
- Key deliverables include executive and operational dashboards, analytical insights and briefs, and user training materials.
Required Experience
- At least 2 years designing and implementing data management solutions.
- A background in public health is advantageous.
Qualifications
- Essential: First university degree in data science, computer science, statistics, applied mathematics, econometrics, or related field.
- Desirable: Master’s degree in data science, computer science, statistics, applied mathematics, econometrics, or related field.
