Senior Clinical Data Manager

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Bioptimus

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2024

🤖 Artificial Intelligence

🧬 Biotechnology

⚕️ Healthcare Insurance

💰 $35M Seed Round on 2024-02

Artificial Intelligence • Biotechnology • Healthcare Insurance

Bioptimus is on a mission to build the first universal AI foundation model for biology, aimed at fueling breakthrough discoveries and accelerating innovations in biomedicine and beyond. The company seeks to transform the biological sciences through advanced artificial intelligence technologies.

📋 Description

• Operate at the intersection of data engineering, clinical science, and partner collaboration across two strategic domains: • Technical conversations with external partners (hospitals, research institutions, CROs/CMOs) and dive into the details of diverse clinical data structures. • 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) and validation frameworks for incoming partner data. • Write production-grade Python code to automate data cleaning and harmonization tasks. • Practical understanding of how clinical data is generated in the real world. • Identify anomalies and hidden biases in incoming data.

🎯 Requirements

• Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Health Informatics, Computer Science, Statistics, or a related quantitative field. Equivalent practical industry experience is highly valued. • 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 a 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)