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About the Role
We are seeking a technical, execution-focused Clinical Data Manager to standardize and harmonize data pipelines, serving as the technical link between unstructured, real-world data and our AI models. You will structure clinical datasets, write reproducible code, enforce incoming data quality control, and design data dictionaries and ontologies for our models within the STELA program.
Responsibilities
- Participate directly in technical conversations with external partners (hospitals, research institutions, CROs/CMOs) to understand data capture, storage, and extraction.
- Translate ambiguous source data into harmonized, AI-ready assets.
- Map and align diverse clinical data to industry-standard biomedical ontologies (e.g., SNOMED, ICD) 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 for incoming partner data.
- Write production-grade Python code to automate data cleaning and harmonization tasks.
- Leverage practical understanding of real-world clinical data generation and identify red flags in incoming data.
- Ask partners the right questions to understand their data structures and audit data for missing variables, anomalies, and biases.
- Recognize important data related to cancer progression metrics and treatment lines.
Requirements
- 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.
- Proven track record of taking messy partner data and building reproducible, production-grade workflows.
- 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.
- 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.
Skills
- Python
- Pandas
- NumPy
- Git
- Clinical data structures
- EHR
- CRFs
- Ontologies
- SNOMED
- ICD
- Oncology
- Immunology
- Data dictionaries
- Data schemas
- Metadata models
- Data quality control
- Data validation
- Data cleaning
- Data harmonization
- AWS
- GCP
- CDISC standards (SDTM/ADaM)
Location
- Remote
Work Type
- Remote
Experience Level
- Senior
Education Level
- Bachelor's degree
- Master's degree
Benefits
- Competitive compensation
- Equity
- Flexibility (remote options)
About the Company
- Bioptimus is building the first universal AI foundation model for biology to fuel breakthrough discoveries and accelerate innovation in biomedicine.
- With more than $75M in funding, Bioptimus is a fast-growing start-up headquartered in Paris, incorporated in October 2023.
- Backed by leading international venture capitalists, our world-class team of scientists and engineers is redefining the frontiers of AI and life sciences.
- 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 growing a world-class team of scientists, engineers, and product leaders.
Equal Opportunity
- We never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, or disability status.
- Decisions related to hiring are made fairly, and we provide equal employment opportunities to all qualified candidates.
- We take responsibility for always striving to create an inclusive environment that makes every employee and candidate feel welcome.