[Hiring] Clinical Data Manager @Bioptimus LinkedIn

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

• Partner Data Engineering & Collaboration
  • 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.
• Data Governance, Quality, and Automation
  • 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 to check incoming partner data for integrity, completeness, and programmatic consistency.
  • Write production-grade Python code to automate data cleaning and harmonization tasks.
• Clinical Reality & Intuition
  • Practical understanding of how clinical data is generated in the real world (hospitals, trials, CROs).
  • Know what questions to ask partners to get to the "ground truth" of their data structures.
  • Familiarity with cancer progression metrics (e.g., RECIST criteria, TNM staging, longitudinal treatment lines like immunotherapy vs. chemotherapy).

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) combined with a modern tech-stack approach.
• 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.

Candidate Journey

• To be considered, please submit your CV in English.
• Screening: A 30-minute introductory call with the Hiring Manager.
• Interviews: Series of interviews including a Data Strategy Panel Presentation, Technical Deep Dive, and Executive Interview.
• Offer: Contingent upon successful completion of a reference check.
• Onboarding: Welcome to the team!