Data Scientist / Data Engineer

About the role

Nucs AI is building AI‑powered tools for cancer diagnostics and treatment planning. We are looking for a Data Scientist / Data Engineer to design and operate robust data pipelines and analytical workflows that support clinical studies and regulatory submissions.

Key responsibilities

• Build auditable, cloud‑based data pipelines for large clinical and medical imaging datasets.
• Conduct statistical analysis of diagnostic performance, model evaluation, and data quality.
• Apply classical machine‑learning, explainable AI, and deep‑learning techniques to solve data problems.
• Automate ontology induction from medical documents using large language models.
• Develop dashboards and data‑observability tools.
• Maintain data lineage, provenance, traceability, and reproducibility across workflows.
• Produce analyses and evidence that satisfy regulatory audits.

Required profile

• Master’s degree or PhD in a quantitative discipline (e.g., computer science, data science, engineering, mathematics, statistics, physics, economics).
• 3+ years of hands‑on data‑engineering experience with production‑grade solutions.
• Proficiency in Python and SQL, and familiarity with Git‑based workflows, automated testing, code reviews, and CI/CD.
• Comfort working with medical imaging formats such as DICOM and NIfTI.
• Practical experience with classical machine learning, explainable ML, deep learning, and modern LLM tooling.
• Experience with cloud data platforms (GCP or equivalent) and strong understanding of data lineage and reproducibility.

Required skills

• Python
• SQL
• Git
• CI/CD
• DICOM
• NIfTI
• Classical machine learning
• Explainable ML
• Deep learning
• Large language models (LLM)
• Google Cloud Platform (GCP) or equivalent cloud infrastructure
• Data lineage, provenance, traceability
• Dashboard development
• Data observability tooling

What we offer

• Opportunity to work at the intersection of AI, medical imaging, and oncology.
• Collaborate with leading medical institutions and pharmaceutical partners worldwide.
• Venture‑backed, early‑stage environment with fast‑paced innovation.