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Data Operations Lead
Data Operations Lead
Bioptimus is building the first universal AI foundation model for biology to fuel breakthrough discoveries and accelerate innovation in biomedicine. With over $75M in funding, Bioptimus is a fast-growing start-up based in Paris, founded in October 2023. Backed by top-tier venture capitalists, our team of scientists and engineers is redefining AI and life sciences.
About the Role
We are hiring a highly organized and technically proficient Data Operations Lead to own and scale the operational lifecycle of biomedical data partnerships. This critical role serves as the bridge between external clinical and research partners, internal Data teams, and the engineering environment that powers our AI foundation models.
What You’ll Be Doing
As Data Operations Lead, you will be responsible for:
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Data Partnership Operations & Lifecycle Management
- Own the operational lifecycle of external data partnerships post-contract.
- Serve as the primary operational and technical point of contact for hospitals, biobanks, CROs, and research laboratories.
- Coordinate onboarding, data delivery timelines, and stakeholder communication to ensure successful execution of partnership milestones.
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Data Transfer & Infrastructure Coordination
- Manage secure biomedical data transfers using cloud infrastructure and standardized transfer protocols.
- Oversee access management, encryption, and ingestion workflows across AWS S3, SFTP, APIs, and direct upload pipelines.
- Ensure datasets are validated, tracked, and compliant with internal governance standards.
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Clinical & Multi-Omics Data Harmonization
- Collaborate with internal technical and product teams to define and maintain harmonized data models and metadata standards.
- Organize relationships between clinical metadata, genomics, transcriptomics, spatial biology, and pathology data.
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Pipeline Operations & Automation
- Work with engineering and data teams to configure and maintain lightweight ingestion and QC pipelines.
- Identify bottlenecks and automate repetitive workflows with scripts, templates, dashboards, or automation tools to improve efficiency and visibility.
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Data Quality Oversight
- Conduct automated and manual QC checks across incoming datasets.
- Identify missing data, inconsistencies, corruption, or metadata mismatches.
- Work with external partners to resolve issues and ensure data integrity, traceability, and version control.
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Operational Tracking & Reporting
- Maintain a centralized "single source of truth" for datasets, including ingestion status, completeness, QC status, and milestone tracking.
- Build and maintain reporting dashboards for project visibility and operational risk monitoring.
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Cross-Functional Collaboration & Communication
- Partner with Data Science, Engineering, Legal, and Partnership teams to align operations with business and scientific priorities.
- Translate technical challenges into clear guidance for both scientific and non-technical stakeholders.
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Site Visits & External Partner Engagement
- Conduct periodic on-site visits to hospitals, biobanks, and labs to support onboarding, troubleshooting, and collaboration strengthening.
What You’ll Bring
The ideal candidate will: ✔ Be highly proactive, organized, and detail-oriented. ✔ Thrive in a fast-paced, evolving environment. ✔ Combine strong project management skills with hands-on technical fluency. ✔ Have experience in biomedical data ecosystems.
Required Skills & Experience
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Biomedical Data Expertise
- Deep understanding of clinical and biomedical data (real-world data, clinical trials, multi-omics).
- Familiarity with oncology, immunology, or related therapeutic areas (highly desirable).
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Cloud & Data Infrastructure
- Proven AWS (S3, CLI, access management) experience.
- Knowledge of secure data transfer protocols and biomedical data handling workflows.
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Data Wrangling & Technical Skills
- Proficiency in Python/R + SQL.
- Ability to write scripts, automate workflows, and interact with cloud APIs.
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Project & Stakeholder Management
- Experience managing multiple external collaborations.
- Strong communication skills for scientific and non-technical stakeholders.
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- Educational Background
- Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Health Informatics, Computer Science, or related field.
Preferred Experience
- Worked directly with hospitals, biobanks, labs, or CROs.
- Knowledge of biomedical standards (GDPR, HIPAA), anonymization, and compliance.
- AWS-powered large-scale biomedical dataset management.
- Digital pathology & multi-omics workflows.
- Handling genomics/transcriptomics formats (FASTQ, BAM, VCF, TIFF).
- Operational tracking tools, dashboards, or workflow automation.
- Cross-functional stakeholder management in complex data projects.
The Candidate Journey
- CV Submission – Apply with an English CV.
- Screening – Review by hiring team for technical fit.
- Interview with Hiring Manager (30 min) – Discuss background, experience, and motivation.
- Technical Assessment – Challenge on data operations, scripting, SQL, and cloud infra.
- Case Study Presentation – Problem-solving exercise with data onboarding/partner management.
- Executive Interview – Alignment on long-term vision and company culture.
- Offer & Onboarding – Final decision followed by offer discussion and onboard integration.
Why This Is a Unique Opportunity
✨ Join a groundbreaking team shaping AI, biotech, and biomedical research. ✨ Critical operational role enabling next-gen biomedical AI foundation models. ✨ Build scalable data infrastructure for AI-driven discovery. ✨ Collaborate globally with leading hospitals, researchers, and engineers.
Perks
- Mission-driven culture with a collaborative workplace.
- Competitive salary + equity rewards.
- Flexible remote/work arrangements.
- Career growth and leadership development.
- Impact on the future of biology and AI.
Bioptimus is committed to diversity, equity, and inclusion (DEI). We provide equal opportunities to all candidates regardless of race, religion, gender identity, sexual orientation, age, marital status, or disability. Our hiring decisions are fair, transparent, and inclusive.
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