Senior Clinical Data Manager

This is a fully remote position, open to applicants in Germany.

📋 Description

• Connect unstructured, real-world data with cutting-edge AI models.

• Act as the technical liaison during discussions with global partners to standardize and harmonize data pipelines.

• Organize clinical datasets within the STELA program.

• Develop reproducible code, implement incoming data quality control (QC), and create data dictionaries and ontologies.

• Engage directly in technical discussions with external partners, including hospitals, research institutions, and CROs/CMOs.

• Convert ambiguous source data into harmonized, AI-ready resources.

• Align and map diverse clinical data to industry-standard biomedical ontologies.

• Create, develop, and maintain data dictionaries, schemas, and metadata models.

• Set up, automate, and enforce data quality control (QC) frameworks.

• Write production-level Python code to automate data cleaning and harmonization processes.

• Conduct audits on data to uncover missing variables, anomalies, and hidden biases.

• Understanding of cancer progression metrics.

⛳️ Requirements

• Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Health Informatics, Computer Science, Statistics, or a related quantitative field.

• Several years (typically 3–5+) of practical experience in clinical data management or clinical data engineering within a CRO, CMO, pharmaceutical, or biotech setting.

• Advanced proficiency in Python and standard data science libraries (e.g., Pandas, NumPy) for data manipulation, cleaning, and validation.

• Proven dedication to code reproducibility, with significant experience in 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, particularly those relevant to cancer/oncology and/or immunology datasets.

• Capability to agree on data delivery formats with partner clinical teams.

• Comfortable working in a dynamic startup environment where data schemas evolve and ingestion requirements must be defined from scratch.

🏝️ Benefits

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