At a Glance
- Tasks: Lead data operations for groundbreaking biomedical AI projects and manage partnerships.
- Company: Join a fast-growing start-up at the forefront of AI and biomedicine.
- Benefits: Enjoy competitive salary, equity, flexible work options, and growth opportunities.
- Other info: Inclusive culture that values diverse perspectives and experiences.
- Why this job: Shape the future of biology and AI while collaborating with top researchers globally.
- Qualifications: Experience in biomedical data, cloud infrastructure, and strong communication skills required.
The predicted salary is between 60000 - 80000 £ per year.
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.
About the role
We are looking for a highly organized and technically proficient Data Operations Lead to own and scale the operational lifecycle of biomedical data partnerships. In this critical role, you will serve as the bridge between external clinical and research partners, our internal Data team, and the engineering environment that powers our AI foundation models.
What you’ll be doing
- Data Partnership Operations & Lifecycle Management: Own the operational lifecycle of external data partnerships following contract signature. Act 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.
- Data Transfer & Infrastructure Coordination: Manage secure biomedical data transfers using cloud infrastructure and standardized transfer protocols. Coordinate access management, encryption, and ingestion workflows across cloud storage systems (AWS S3, SFTP, APIs, direct upload pipelines). Ensure incoming datasets are delivered, validated, and tracked according to internal governance standards.
- Clinical & Multi‑Omics Data Harmonization: Collaborate with internal technical and product teams to define and maintain harmonized data models and metadata standards across complex clinical and multi‑modal datasets. Organize and maintain relationships between clinical metadata and associated omics or imaging assets, including genomics, transcriptomics, spatial biology, and pathology data.
- Pipeline Operations & Automation: Work closely with engineering and data teams to configure and maintain lightweight ingestion and QC pipelines. Identify operational bottlenecks and repetitive workflows and convert them into scalable systems, scripts, templates, dashboards, or automation tools that improve operational efficiency and visibility.
- Data Quality Oversight: Coordinate automated and manual quality control checks across incoming datasets. Identify missing data, inconsistencies, corruption, or metadata mismatches and work directly with external partners to resolve issues. Ensure data integrity, traceability, and version control throughout the ingestion process.
- Operational Tracking & Reporting: Maintain a centralized “single source of truth” for all incoming datasets, including ingestion status, completeness, QC status, and milestone tracking. Build and maintain reporting dashboards and operational tools to provide visibility into project progress, ingestion velocity, and operational risks.
- Cross‑Functional Collaboration & Communication: Partner closely with Data Science, Engineering, Legal, and Partnership teams to align operational execution with business and scientific priorities. Communicate technical issues clearly to both scientific collaborators and non‑technical stakeholders. Provide regular updates on operational risks, blockers, and delivery progress.
- Site Visits & External Partner Engagement: Conduct periodic visits to partner hospitals, biobanks, and laboratories to support onboarding, troubleshoot technical or operational bottlenecks, and strengthen long‑term collaborations.
What you’ll bring
- Biomedical Data Expertise: Strong understanding of clinical and biomedical data structures, including real‑world data, clinical trial datasets, and multi‑omics data modalities. Familiarity with oncology, immunology, or related therapeutic areas is highly desirable.
- Cloud & Data Infrastructure: Proven experience managing data lifecycles in cloud environments, particularly AWS (S3, CLI, access management). Familiarity with secure data transfer protocols and large‑scale biomedical data handling workflows.
- Data Wrangling & Technical Skills: Proficiency in Python or R, along with SQL for querying and transforming datasets. Ability to write lightweight scripts, automate workflows, and interact with APIs or cloud‑based systems.
- Project & Stakeholder Management: Demonstrated ability to manage multiple external collaborations and operational workstreams simultaneously. Excellent communication skills, with the ability to translate technical issues into clear guidance for both scientific and non‑technical stakeholders.
- Operational Problem Solving: Comfortable working independently in ambiguous environments. Strong analytical and organizational skills with the ability to identify bottlenecks, improve processes, and drive operational efficiency.
- Educational Background: Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Health Informatics, Computer Science, or a related quantitative field.
How to stand out
- Experience working directly with hospitals, biobanks, laboratories, or clinical research organizations.
- Familiarity with biomedical data standards, anonymization, and compliance frameworks (GDPR, HIPAA).
- Experience managing large‑scale biomedical datasets in cloud environments, particularly AWS.
- Knowledge of digital pathology and/or multi‑omics data workflows.
- Experience handling genomics and transcriptomics file formats (e.g. FASTQ, BAM, VCF, TIFF).
- Experience building operational tracking tools, dashboards, or reporting systems.
- Experience automating operational workflows using scripts, APIs, or lightweight pipelines.
- Proven ability to manage cross‑functional and external stakeholder relationships in complex data projects.
Why This is a Unique Opportunity
- Be part of a trailblazing team working at the intersection of AI, biotech, and biomedical research.
- Play a key operational role in enabling the development of frontier foundation models for biology.
- Build and scale the data infrastructure and operational processes powering next‑generation biomedical AI.
- Collaborate with leading hospitals, biobanks, researchers, and engineers across the globe.
- A collaborative and mission‑driven work environment.
- Competitive salary and equity package.
- Flexible work arrangements, including remote options.
- Opportunities for professional growth and leadership development.
- The opportunity to shape the future of biology and AI through groundbreaking work.
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.
Data Operations Lead employer: Bioptimus
Bioptimus is an exceptional employer, offering a unique opportunity to work at the forefront of AI and biomedicine in a collaborative and mission-driven environment. With competitive salaries, flexible work arrangements, and a strong focus on professional growth, employees are empowered to shape the future of biology and AI while engaging with leading hospitals and researchers globally. Join us in redefining the frontiers of life sciences and enjoy the benefits of being part of a diverse and inclusive team that values every individual's contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Operations Lead
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those connected to Bioptimus. Use LinkedIn to connect with current employees and ask for insights about the company culture and the role.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Since this role involves data operations, be ready to discuss your experience with cloud infrastructure and data management tools. Show us you know your stuff!
✨Tip Number 3
Don’t just talk about your past experiences; relate them to the job description. Highlight how your skills in managing biomedical data and collaborating with cross-functional teams make you the perfect fit for the Data Operations Lead role.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in being part of our mission at Bioptimus.
We think you need these skills to ace Data Operations Lead
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with biomedical data and cloud infrastructure. We want to see how your skills align with the Data Operations Lead role, so don’t hold back on showcasing relevant projects!
Show Off Your Technical Skills:Since this role requires a strong grasp of Python, R, and SQL, be sure to mention any specific projects where you’ve used these tools. We love seeing practical examples of how you've tackled data challenges in the past!
Communicate Clearly:Remember, you’ll be the bridge between technical and non-technical teams. Use clear and concise language in your application to demonstrate your ability to communicate complex ideas effectively. We’re looking for someone who can make tech talk accessible!
Apply Through Our Website:We encourage you to submit your application directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Bioptimus
✨Know Your Data Inside Out
Make sure you have a solid understanding of clinical and biomedical data structures. Brush up on real-world data, clinical trial datasets, and multi-omics data modalities. Being able to discuss these topics confidently will show that you're the right fit for the Data Operations Lead role.
✨Familiarise Yourself with Cloud Infrastructure
Since you'll be managing data lifecycles in cloud environments, particularly AWS, it's crucial to know your way around S3, access management, and secure data transfer protocols. Prepare to discuss your experience with these tools and how you've used them in past roles.
✨Showcase Your Problem-Solving Skills
Be ready to share examples of how you've identified operational bottlenecks and improved processes in previous positions. Highlight any experience you have with automating workflows or using scripts to enhance efficiency—this will demonstrate your ability to thrive in ambiguous environments.
✨Communicate Clearly with Stakeholders
As a bridge between technical and non-technical teams, your communication skills are key. Practice explaining complex technical issues in simple terms. Be prepared to discuss how you've managed cross-functional relationships and kept stakeholders informed about project progress and risks.