About Qorium

Qorium is a revolutionary biotech and tissue engineering company that makes fantastic, real leather. Qorium’s cutting edge science provides three primary benefits:

Real Leather: Uniform and tunable leather that can provide better product performance than animal-derived leather
Improved Manufacturability: With consistent, standard sheets, Qorium’s leather improves manufacturing, reducing cost and creating a better final product
Reduced Harm & Sustainability: Dramatically reducing the negative aspects of the leather supply chain. There are no links to the meat industry, no animal suffering, no deforestation, no methane emissions and significantly reduced water, energy, and chemical usage. Qorium’s supply chain is fully traceable.

Founded by three well-regarded founders, Qorium is built upon a unique combination of scientific expertise, leather industry experience, and global business acumen. Backed by leading investors, Sofinnova Partners, Brightlands Venture Partners, Invest NL and LIOF, Qorium has made a great deal of progress since its activation in 2021 and is accelerating its development forward. Overall, Qorium is committed to creating a better product and a better planet and is well positioned to do so.

Position

Qorium is seeking an experienced and hands-on Head of Data Science to lead the implementation and ongoing development of AI and machine learning capabilities across its R&D and Bioprocess functions. This is a pivotal role that sits at the intersection of data science, biotechnology, and business strategy.

Qorium is undertaking an ambitious program to accelerate and improve its go to market with a new data-driven, AI capability that can accelerate lab discoveries, industrial scale-up, and ultimately assist in delivering its product at commercially compelling quality, scale, and price. The program has been scoped and initiated. The company is now seeking an exceptional individual to take ownership of this work internally.

The ideal candidate combines strong technical expertise in machine learning and data science with the strategic vision to guide an AI transformation in a biotech setting. Significant biology experience is important.

This person must be equally comfortable building and deploying models as they are setting an AI roadmap. They will partner closely with various R&D teams, and vendors to execute on a portfolio of use cases ranging from foundational data infrastructure through to advanced predictive modelling and prospective experimental design.

In addition to the hands-on model and strategic work, the role will work closely with Qorium’s Executive Team and its Board of Directors to continue the ongoing strategic planning in this space and the cultural evolution within the company to maximize outcomes. Integrating data science and AI into all processes will require careful planning with and education for all employees.

The Head of Data Science has four primary responsibilities requiring both hands-on execution and strategic leadership:

Own and execute Qorium’s AI/ML implementation roadmap across R&D and Bioprocess
Build and maintain the data and infrastructure foundations required for AI-enabled R&D
Develop and deploy machine learning models and analytics to accelerate scientific discovery
Partner with wet lab scientists to integrate data science into experimental workflows

1) AI/ML Strategy & Execution

Take ownership of Qorium’s AI-enablement program.
Refine and execute the prioritized use case roadmap spanning foundational infrastructure, computer vision, retrospective data analysis, prospective experimental design, and process fingerprinting
Develop workflows and data acquisition strategies optimized for AI implementation
Lead build vs. buy assessments for AI tools and vendor solutions, ensuring future-proof, platform-agnostic decision-making
Leverage, integrate and maintain Qorium’s LIMS knowledge base ensuring the digestion and integration of experimental data, literature, decisions, and meeting context, etc. all queryable in natural language
Track and report on key performance indicators and value metrics for all AI/data science initiatives to leadership and the Board

2) Data Foundations & Infrastructure

Set the foundations of the data science function and evolve the vision and roadmap to keep up to date with the rapid developments in AI for science, including lab automation and screening
Oversee the development, management and governance of Qorium’s data model covering the full process from primary cells through tanning
Manage the cloud-based AI/ML infrastructure (compute, storage, access policies, backup) in collaboration with external engineering resources
Design and implement ETL (Extraction, Transformation, Load) pipelines to automate data ingestion from instruments, Benchling (LIMS), and legacy sources, replacing Excel-based workflows
Ensure all data practices adhere to FAIR principles (Findable, Accessible, Interoperable, Reusable) and support long-term AI leverage
Lead the integration and annotation of legacy experimental data to enable retrospective analyses and model training

3) Hands-On Data Science & Machine Learning

Develop, train, validate, and deploy machine learning models
Conduct retrospective analyses of PAST experiments to identify performance drivers, map design spaces, and generate data-driven hypotheses
Implement prospective experimental design methods (Bayesian optimization, adaptive DoE, Response Surface Methodology) to guide process optimization
Contribute to the development of a semantic orchestration layer (knowledge graphs, ontologies, vector search) to enable complex cross-domain queries
Establish MLOps pipelines for model deployment, monitoring, retraining, and version control

4) Cross-Functional Collaboration & Scientific Partnership

Work as an embedded partner within the various R&D teams to jointly devise research strategies, exploring methods, and interpreting results
Identify and close learning loops between currently sequential processes, connecting upstream experimental decisions to downstream outcomes
Translate scientific priorities and business objectives into data science workplans and communicate data science findings to non-technical stakeholders
Manage relationships with external AI consultants, fractional engineering resources, and potential technology vendors
Support the Benchling LIMS implementation to ensure configurations meet current and future AI/ML requirements, including API access, schema flexibility, and ontology alignment
Champion a culture of data-driven experimentation and support team adoption of new tools and ways of working

Required Qualifications

MSc or PhD in Data Science, Machine Learning, Computational Biology, Bioinformatics, or a related quantitative field
7+ years’ hands-on experience in applied machine learning and data science, with demonstrable experience building and deploying ML models in production environments
Strong proficiency in Python and the ML/data science stack (e.g. scikit-learn, PyTorch/TensorFlow, pandas, NumPy) as well as data engineering tools
Experience with computer vision / image analysis, ideally in a biological or medical context
Familiarity with statistical experimental design methods (DoE, Bayesian optimization, Response Surface Methodology)
Experience with cloud infrastructure (AWS or Azure), including compute, storage, and deployment pipelines
Proven ability to work cross-functionally with scientific or technical teams, translating domain problems into data science solutions
Strong communication skills with the ability to present complex analytical work to non-technical leadership
Self-directed and comfortable operating as an individual contributor while also setting strategic direction
Mission-driven and passionate about sustainability, animal welfare, and/or the potential of biotechnology
Ability to work effectively in a fast-paced, innovative startup environment; comfortable with ambiguity and able to pivot as required by the business
Fluency in English (both written and spoken). Dutch language skills not required.
Authorization to work in the Netherlands; sponsorship available for suitable candidates

Preferred Qualifications

Experience in an AI-native or AI-first biotech, synthetic biology, or cellular agriculture company
Familiarity with LIMS platforms (particularly Benchling) and laboratory data workflows
Experience building or working with knowledge graphs, ontologies, and semantic data layers
Understanding of biological processes such as bioprocessing, cell culture, and/or tissue engineering workflows
Experience with multivariate process analysis (MSPC, PCA, PLS) in a bioprocess or manufacturing context
Exposure to MLOps frameworks and CI/CD for machine learning systems
Understanding of lab automation and screening platforms
Experience managing or mentoring junior data scientists or working with fractional/contract technical resources

Benefits

Qorium offers competitive compensation and benefits including equity participation.

Location & Office Plan

Qorium is based in Maastricht, in the southern Netherlands. About two hours from Amsterdam and one hour from Brussels and Cologne. Maastricht is a well-regarded high-tech hub with an impressive startup cluster. The Head of Data Science is expected to work in the Qorium offices three days a week on average. Close collaboration with the lab-based scientific teams is essential to this role.

How to apply

Send your CV with cover letter to HR, Pia Tijssen: pia.tijssen@qorium.com

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Head of Data Science

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