Overview

EDDC is Singapore's national drug discovery platform, working with public and industry partners to advance novel therapeutics in oncology, inflammatory and autoimmune diseases. We are seeking a driven Data Scientist to join the AI/ML for Drug Discovery group, someone with strong analytical capabilities, biological understanding, and systems-level thinking about data, able to lead work end-to-end with scientific and commercial impact. We welcome applicants from bioinformatics, data science, or data engineering backgrounds. What matters is the ability to reason across biological questions and data infrastructure, apply AI tools fluently, and contribute to shaping the group's scientific direction.

Responsibilities

• Develop and apply computational methods to analyse diverse biological datasets, including genomics, transcriptomics (bulk, single-cell, and spatial RNA-seq), and proteomics, connecting findings directly to target identification and mechanism-of-action studies.
• Build and deploy machine learning and AI models to uncover biological patterns, prioritise therapeutic targets, and generate biomarker hypotheses that advance the drug discovery pipeline.
• Apply systems thinking to understand and optimise the full data lifecycle, from how biological, clinical, and commercial data is generated, structured, and ingested, to how analytical outputs are deployed and consumed, bridging data infrastructure, analytics, and decision-making.
• Collaborate closely with biologists, chemists, clinicians, and project leads to integrate scientific, clinical, and commercial data into de-risking frameworks that support project prioritisation, elevation, and pipeline decisions.
• Proactively adopt and integrate agentic AI tools, including LLM-assisted coding, automated analysis pipelines, and AI-driven literature synthesis - to accelerate your own and the team's throughput, championing AI-augmented working and continuously improving in-house workflows and platforms.
• Own computational projects end-to-end, from problem scoping through to delivery, bringing product thinking to prioritise work by impact, and communicating results clearly to senior leadership and cross-functional stakeholders.
• Build and manage relationships with external partners in computational biology and AI, ensuring alignment with internal priorities, milestone delivery, and translating complex findings into clear narratives that influence strategic decisions.

Requirements

• PhD in a relevant quantitative or biological field, or equivalent industry experience demonstrating the same depth and capability.
• Demonstrated experience working with complex biological and multi-omics datasets, such as genomics, transcriptomics, and proteomics, with sufficient biological foundation to engage credibly with scientists and ask the right questions of the data.
• Proficiency in Python and R, with an understanding of data infrastructure including cloud-based and on-premises systems, APIs, databases, and workflow frameworks.
• Demonstrated ability to lead projects end-to-end, communicate findings clearly to technical and non-technical stakeholders, and influence decisions in a fast-moving, cross-functional environment.
• A genuine enthusiasm for AI-augmented working - comfortable adopting and experimenting with agentic AI tools as part of everyday practice.
• Hands-on experience with machine learning, biological foundation models (nucleotide, protein, or cell models), or agentic AI pipelines in a research or industry context is an advantage.
• Experience in pharmaceutical or biotech companies is an advantage.