Senior Clinical Data Manager

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Bioptimus

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

🤖 Artificial Intelligence

🧬 Biotechnology

☁️ SaaS

💰 $41M Series A - Bioptimus on 2025-01

Artificial Intelligence • Biotechnology • SaaS

Bioptimus is a company that builds foundation AI models for biology, integrating multimodal and multiscale biological data to break down data silos and accelerate biomedical research and clinical decision‑making. Its flagship models include H‑Optimus‑1 for histology/digital pathology and M‑Optimus as a universal biology model; the company partners with research institutions, clinical practices, and industry to train and deploy models securely at scale. Founded in Paris in 2024, Bioptimus focuses on applying AI to problems across biomedical research, clinical workflows, and life‑science R&D while emphasizing data quality, security, and scientific validation.

📋 Description

• Bridge the gap between unstructured, real-world data, and frontier AI models • Serve as the technical link during conversations with global partners to standardise and harmonise data pipelines • Structure clinical datasets within the STELA program • Write reproducible code, enforce incoming data QC, and design data dictionaries and ontologies • 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 • Design, build, and maintain data dictionaries, schemas, and metadata models • Establish, automate, and enforce data quality control (QC) frameworks • Write production-grade Python code to automate data cleaning and harmonization tasks • Actively audit data to identify missing variables, anomalies, and hidden biases • Familiarity with cancer progression metrics.

🎯 Requirements

• Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Health Informatics, Computer Science, Statistics, or 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) for data manipulation, cleaning, and validation • Demonstrated commitment to code reproducibility, including strong experience with Git version control and building reusable data pipelines • 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 where data schemas evolve and ingest requirements must be defined from scratch.

🏖️ Benefits

• Competitive compensation, equity, and flexibility (remote options)