Data Operations Lead

Company Overview

Bioptimus is innovating in the biomedical space by developing the first universal AI foundation model tailored for biology. Established in October 2023 and supported by over $75 million in funding from prominent global venture capitalists, Bioptimus combines the expertise of esteemed scientists and engineers to push the boundaries of AI and life sciences research. The company is headquartered in Paris but offers this position fully remote.

Role Summary

The Data Operations Lead will be a pivotal figure responsible for overseeing and expanding the operational workflow of biomedical data partnerships. Acting as the central liaison between external clinical and research collaborators, internal Data teams, and engineering groups supporting AI model development, this role demands technical proficiency, exceptional organization, and proactive engagement.

Key Responsibilities

• Manage the end-to-end operational lifecycle of external biomedical data partnerships post-contract initiation, serving as the prime contact for hospitals, biobanks, CROs, and research labs, coordinating onboarding and ensuring milestone deliverables.
• Oversee secure biomedical data transfers using cloud-based systems such as AWS S3, SFTP, APIs, and other upload pipelines, ensuring data validation, governance compliance, and meticulous tracking.
• Collaborate internally to harmonize clinical and multi-omics datasets by establishing consistent data models and metadata standards that integrate clinical information with various omics and imaging data.
• Partner with engineering and data teams to maintain ingestion and quality control pipelines, identifying repetitive manual tasks and developing automation tools, scripts, dashboards, and systems to enhance operational effectiveness.
• Supervise both automated and manual quality assurance procedures to detect and rectify missing, inconsistent, or corrupted data with relevant partners, maintaining data integrity and version control throughout.
• Maintain centralized, comprehensive data tracking systems and build reporting tools to monitor project progress, data ingestion rates, and operational risks.
• Foster productive communication and collaboration across cross-functional teams including Data Science, Engineering, Legal, and Partnerships, clearly conveying technical issues to both technical and non-technical stakeholders and providing frequent updates on operational status.
• Conduct site visits to partner institutions such as hospitals, biobanks, and labs to support onboarding, troubleshoot challenges, and strengthen relationships.

Candidate Profile

• Strong knowledge of biomedical and clinical data frameworks, including real-world data, clinical trial materials, and multi-omics modalities, ideally with background in oncology, immunology, or similar therapeutic areas.
• Experience managing extensive data lifecycles in cloud environments, particularly AWS services like S3 and CLI, combined with familiarity with secure transfer protocols and large-scale biomedical data workflows.
• Technical proficiency with Python programming and SQL queries for data manipulation, automation of workflows, and managing APIs or cloud storages.
• Ability to manage multiple stakeholder collaborations and operational streams simultaneously with excellent communication skills to translate complex concepts into accessible language.
• Strong analytical and problem-solving abilities, self-motivation to thrive independently in dynamic settings, and capability to optimize processes and workflows.
• Educational qualifications including Bachelor’s or Master’s degrees in Life Sciences, Bioinformatics, Health Informatics, Computer Science, or related quantitative disciplines.

Distinctive Advantages

• Previous hands-on experience collaborating directly with hospitals, biobanks, clinical research laboratories, or CROs.
• Familiarity with biomedical data privacy, anonymization techniques, and compliance standards such as GDPR and HIPAA.
• Expertise in managing complex biomedical datasets, including genomic and transcriptomic files (e.g., FASTQ, BAM, VCF, TIFF), within cloud infrastructures.
• Knowledge of digital pathology and multi-omics data processing pipelines.
• Proven track record creating operational dashboards, tracking systems, and automated workflows.
• Experience liaising and managing relationships across cross-functional teams and external collaborators.

Selection Process

• Initial screening of applications based on alignment with role requirements.
• Interview with Hiring Manager focusing on operational background, technical knowledge, and motivation.
• Technical assessment involving practical exercises in data management, scripting, SQL, cloud infrastructure, and problem-solving.
• Case study presentation addressing biomedical data onboarding or partner management scenarios.
• Final interview with Senior Leadership covering vision alignment, collaboration preferences, and culture fit.
• Offer stage and onboarding upon acceptance.

Why Join Bioptimus?

• Engage with a pioneering team working at the nexus of artificial intelligence, biotechnology, and biomedical research.
• Take a leadership role in operationalizing cutting-edge data infrastructure powering next-generation AI foundation models for biology.
• Collaborate globally with top-tier hospitals, research repositories, and engineering teams.
• Enjoy a supportive, mission-oriented workplace with competitive pay, equity options, flexible remote work, and growth opportunities.

Equal Opportunity Commitment

Bioptimus values diversity and inclusion, ensuring equitable hiring without discrimination based on race, religion, gender, nationality, sexual orientation, age, disability, or other protected characteristics. The company fosters an inclusive culture where every team member and applicant is welcomed and respected.