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Salary: £80,000 – £100,000
Our client is a Series A BioTech startup that has recently raised £9M to accelerate the development of next-generation therapies and breakthrough discoveries.
By harnessing advanced data science, machine learning, and biotechnology, they’re unlocking new insights into biology that will drive innovation in healthcare and improve patient outcomes worldwide.
This is an exciting opportunity to join an early-stage, mission-driven team at the forefront of computational biology. With data at the core of their strategy, you’ll play a critical role in shaping how science and technology intersect to deliver meaningful impact.
Why Join?
- Impact – Your work will directly contribute to life-changing innovations in biotech, from discovery through to development.
- Innovation – Apply cutting-edge data science to some of the hardest problems in biology, combining computational methods with experimental research.
- Growth – As part of a scaling Series A company, you’ll gain ownership, exposure, and the chance to help define the future data science function.
About the Role
We are seeking a Data Scientist to join the growing team. You’ll design, implement, and optimise machine learning models and analytical workflows to extract insights from complex biological datasets. Your work will accelerate R&D, optimise experiments, and support the development of new biotech products and therapies.
This role is ideal for someone who thrives in a fast-paced, collaborative environment and is motivated to apply data-driven approaches to solve real-world biological challenges.
Key Responsibilities
Data Modelling & Analysis
- Build and apply machine learning and statistical models to biological datasets (genomics, transcriptomics, imaging, clinical, etc.).
- Develop predictive models to guide experimental design and inform decision-making.
- Perform statistical analysis and ensure robust validation of results.
Collaboration & Delivery
- Work closely with biologists, engineers, and clinicians to translate scientific challenges into computational solutions.
- Communicate findings to both technical and non-technical stakeholders through clear reports and visualisations.
- Contribute insights that shape R&D direction and product development.
Infrastructure & Tools
- Improve data pipelines and ensure data integrity in collaboration with engineering teams.
- Help shape the company’s data science toolkit, best practices, and standards.
- Document models, workflows, and methodologies to ensure reproducibility.
Required Qualifications
Technical Skills
- Degree (Master’s/PhD preferred) in Data Science, Statistics, Computer Science, Computational Biology, or a related field.
- Proficiency in Python and/or R, plus SQL for handling large datasets.
- Strong knowledge of statistical modelling, machine learning, and data visualisation.
- Experience with BI or data science tools (e.g. Jupyter, Tableau, Power BI, Looker).
- Bonus: familiarity with biological datasets (genomics, proteomics, clinical).
Business & Science Acumen
- Ability to frame biological research questions into data science problems.
- Strong grasp of experimental design and statistical validation.
- Experience in fast-paced, research-driven environments.
Soft Skills
- Excellent communicator, able to translate complex insights clearly.
- Highly detail-oriented with strong problem-solving ability.
- Comfortable working independently and in collaborative cross-functional teams.
- Motivated by the challenges and opportunities of an early-stage startup.
Preferred Qualifications
- Experience working in a biotech, life sciences, or healthcare data setting.
- Familiarity with cloud platforms (AWS, GCP, Azure).
- Knowledge of data engineering, pipelines, or workflow automation.
- Previous experience in a startup environment (Series A–B).
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