[Hiring] Clinical Data Manager @Bioptimus

Role Description

Bioptimus’ mission is to accelerate biomedical innovation by building the reference foundation model of biology that will unlock AI superpowers for the biomedical ecosystem. We are looking for a technical, execution-focused Clinical Data Manager to bridge the gap between unstructured, real-world data, and our frontier AI models.

In this role, you will be the authority on clinical data structures, serving as the technical link during conversations with our global partners to standardise and harmonise data pipelines.

Operating within our STELA program, you will structure our clinical datasets. You are a hands-on technical expert who writes reproducible code, enforces incoming data QC, and designs the data dictionaries and ontologies for our models.

What you'll be doing

• Participate directly in technical conversations with external partners (hospitals, research institutions, CROs/CMOs).
• Translate ambiguous source data into harmonized, AI-ready assets.
• Map and align diverse clinical data to industry-standard biomedical ontologies (e.g., SNOMED, ICD, etc…) with an emphasis on clinical oncology and immunology data.
• Design, build, and maintain data dictionaries, schemas, and metadata models that align with STELA’s multimodal pipeline requirements.
• Establish, automate, and enforce data quality control (QC) and validation frameworks.
• Write production-grade Python code to automate data cleaning and harmonization tasks.
• Understand how clinical data is generated in the real world and recognize gaps between ideal protocols and messy clinical realities.
• Audit data to find missing variables, anomalies, and hidden biases.
• Familiarity with cancer progression metrics to recognize important data.

Qualifications

• Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Health Informatics, Computer Science, Statistics, or a related quantitative field.
• A few years (typically 3–5+) of hands-on experience in clinical data management or clinical data engineering within a CRO, CMO, pharma, or biotech environment.
• High proficiency in Python and standard data science libraries (e.g., Pandas, NumPy).
• Demonstrated commitment to code reproducibility, including strong experience with Git version control.
• Familiarity with clinical data structures, electronic health records (EHR), case report forms (CRFs), and longitudinal clinical trial data.
• Knowledge of standard clinical and biological ontologies, specifically those tailored to cancer/oncology and/or immunology datasets.
• Ability to align on data delivery formats with partner clinical teams.
• Comfort working in a fast-paced startup environment.

Requirements

• Experience with cloud computing platforms (AWS, GCP, etc…)
• Experience working directly with multimodal datasets.
• Understanding of CDISC standards (SDTM/ADaM).
• Experience building or optimizing ETL pipelines for large-scale biobanks or multinational clinical consortia.

Benefits

• Join a mission-driven team redefining biology through AI.
• Work in a collaborative, high-autonomy, high-impact environment.
• Contribute to pioneering research, infrastructure, or strategy at the ground floor.
• Competitive compensation, equity, and flexibility (remote options).
• Help shape the scientific and technical culture of a category-defining company.

The candidate journey

• Submit your CV in English.
• 30-minute introductory call with the Hiring Manager.
• Data Strategy Panel Presentation (45 min).
• Technical Deep Dive (30 min).
• Executive Interview (30 min).
• Offer contingent upon successful completion of a reference check.
• Onboarding to get you fully integrated at Bioptimus.