Bioptimus - Clinical Data Manager (Senior)
Requirements
• The successful candidate will have a ‘team-first’ attitude; be independent, curious, and detail-oriented; thrive in a dynamic, fast-paced environment; and be fun to work with. You possess the rare ability to confidently lead complex technical alignment meetings with partners while simultaneously being excited to roll up your sleeves and write code. • Educational Background: 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. • Educational Background: • Industry Experience: 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. • Hands-on Coding Skills: High proficiency in Python and standard data science libraries (e.g., Pandas, NumPy) for data manipulation, cleaning, and validation. • Software Best Practices: Demonstrated commitment to code reproducibility, including strong experience with Git version control and building reusable data pipelines. • Software Best Practices: • Clinical Data Expertise: Familiarity with clinical data structures, electronic health records (EHR), case report forms (CRFs), and longitudinal clinical trial data. • Clinical Data Expertise: • Ontologies & Vocabularies: Knowledge of standard clinical and biological ontologies, specifically those tailored to cancer/oncology and/or immunology datasets. • Ontologies & Vocabularies: • cancer/oncology • Communication & Alignment: Ability to align on data delivery formats with a partner clinical teams. • Communication & Alignment: • Start-up experience: Comfort working in a fast-paced startup environment where data schemas evolve and ingest requirements must be defined from scratch. • How to stand out • How to stand out • Experience with cloud computing platforms (AWS, GCP, etc…) • Experience working directly with multimodal datasets (e.g., matching clinical records with omics or digital pathology imaging). • Understanding of CDISC standards (SDTM/ADaM) combined with a modern tech-stack approach (beyond legacy SAS programming). • Experience building or optimizing ETL pipelines for large-scale biobanks or multinational clinical consortia. • The candidate journey • To be considered, please submit your CV in English. We believe in a transparent and collaborative interview process. Here is what you can expect after submitting your application: • please submit your CV in English • Screening: A 30-minute introductory call with the Hiring Manager to discuss your background, motivations, and the position in more detail. • Screening: • Interviews: • Data Strategy Panel Presentation (45 min): You will present a short overview of a past data management challenge you overcame (e.g., designing a complex data dictionary or aligning messy CRO data), followed by Q&A. • Data Strategy Panel Presentation (45 min): • Technical Deep Dive (30 min) - There will be 1 additional break out session to do a deep dive with 1-2 Bioptimus Engineers • Technical Deep Dive (30 min) • Executive Interview (30 min): A discussion with member(s) of our Senior Leadership focusing on long-term vision, cultural fit, and mutual potential. • Executive Interview (30 min): • Offer: Following the completion of all interviews, our hiring team will make a final decision. Please note that an offer is contingent upon the successful completion of a reference check. • Offer: • Onboarding: Welcome to the team! We will begin your onboarding to get you fully integrated at Bioptimus! • Onboarding:
Responsibilities
• As our Clinical Data Manager, you will operate at the intersection of data engineering, clinical science, and partner collaboration across two strategic domains: • Partner Data Engineering & Collaboration • Technical Partner Interface: Participate directly in technical conversations with external partners (hospitals, research institutions, CROs/CMOs). Dive into the details of diverse clinical data structures to understand how data is captured, stored, and extracted. • Technical Partner Interface: • Order from Uncertainty: Translate ambiguous source data into harmonized, AI-ready assets. • Order from Uncertainty: • Ontology Integration: 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. • Ontology Integration: • Data Governance, Quality, and Automation • Data Dictionary Architecture: Design, build, and maintain data dictionaries, schemas, and metadata models that align with STELA’s multimodal pipeline requirements, while ensuring integration with existing pipelines. • Data Dictionary Architecture: • Enforcing Ingest Quality: Establish, automate, and enforce data quality control (QC) and validation frameworks to check incoming partner data for integrity, completeness, and programmatic consistency. • Enforcing Ingest Quality: • Reproducible Pipeline Code: Write production-grade Python code to automate data cleaning and harmonization tasks. • Reproducible Pipeline Code: • Clinical Reality & Intuition • Clinical Reality: Practical understanding of how clinical data is generated in the real world (hospitals, trials, CROs). You understand the gaps between ideal protocols and messy clinical realities, and you know what red flags to look for in incoming data. • Clinical Reality: • The Investigative Mindset: You know what questions to ask partners to get to the "ground truth" of their data structures. Actively audit data to find missing variables, anomalies, and hidden biases. • The Investigative Mindset: • Oncology/Immunology Domain Knowledge: Familiarity with cancer progression metrics (e.g., RECIST criteria, TNM staging, longitudinal treatment lines like immunotherapy vs. chemotherapy) so you can recognize what data is important. • Oncology/Immunology Domain Knowledge:
Benefits
• 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. • We believe that the unique contributions of all Bioptimists create our success. To ensure that our culture continues to incorporate everyone’s perspectives and experience, 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.
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT