Job Title: Senior Data Scientist – Healthcare & Biotech Analytics
Location: Cambridge (Hybrid - 1 day a week onsite)
Salary: £70,000 - £100,000 + benefits
About the Company:
Join an innovative, fast-growing biotech company revolutionizing precision medicine and biomedical research. Our client leverages advanced data science and machine learning to accelerate drug discovery, optimise patient outcomes, and uncover breakthroughs in disease understanding. Backed by top-tier healthcare investors, they collaborate with leading researchers, clinicians, and pharmaceutical companies to drive data-powered healthcare innovation.
We’re seeking a passionate Senior Data Scientist to join the team and contribute to life-changing research and development initiatives. You’ll work cross-functionally with clinical experts, geneticists, and AI specialists to build cutting-edge data models and derive actionable insights from multi-modal biomedical datasets — from genomics and clinical trials to patient records and real-world evidence.
Key Responsibilities:
* Develop and deploy predictive models for drug discovery, disease progression analysis, and personalized medicine strategies.
* Analyze complex biological, clinical, and genomic datasets to uncover insights that improve diagnostics, treatments, and patient care.
* Build and optimize machine learning pipelines for feature engineering, model training, and validation at scale.
* Work with domain experts to translate research hypotheses into data-driven approaches and insights.
* Stay at the forefront of data science and healthcare AI, proposing new tools and methodologies to enhance capabilities.
* Mentor junior data scientists and collaborate across data, research, and engineering teams.
Essential Skills & Experience:
* Strong programming skills: Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow), R, SQL.
* Deep knowledge of biomedical datasets: Electronic Health Records (EHR), genomics, proteomics, imaging data, clinical trials, or similar.
* Expertise in statistical modeling and machine learning techniques: survival analysis, clustering, regression, decision trees, time-to-event modeling, random forests, and ensemble methods.
* Data engineering proficiency: ETL pipelines, data wrangling, feature extraction, and working with structured/unstructured data.
* Experience with cloud platforms (AWS, GCP, Azure) and data processing frameworks (Spark, Dask, or similar).
* Proficiency in data visualization tools: Matplotlib, Seaborn, Plotly, or BI tools like Tableau and Power BI.
* Strong communication skills — ability to translate complex analysis into actionable insights for non-technical stakeholders (e.g., clinicians, researchers).
* PhD or Master’s in a relevant field — Data Science, Bioinformatics, Biostatistics, Computational Biology, or similar.
Desirable (Bonus) Skills:
* Experience with multi-omics data (genomics, transcriptomics, proteomics, metabolomics).
* Knowledge of NLP techniques — particularly for analyzing medical records or scientific literature.
* Familiarity with Bayesian statistics or causal inference methods.
* Experience with federated learning or privacy-preserving data science (helpful for multi-institution data collaboration).
* Knowledge of regulatory frameworks like GDPR, HIPAA, or MHRA compliance for healthcare data.
* Software engineering best practices — CI/CD pipelines, version control (Git), Docker, or Kubernetes.
* Experience with biological pathway analysis or genetic variant interpretation.
Why Join?
* Make an impact: Your work directly supports scientific breakthroughs and improves patient outcomes.
* Cutting-edge projects: Work on high-impact R&D initiatives, from personalized medicine to multi-omics analysis.
* Career growth: Be part of a growing company that invests in learning, development, and leadership opportunities.
* Collaborative culture: Work alongside world-leading scientists, data experts, and biotech innovators.
What We Offer:
* Competitive salary and equity options.
* Opportunities to work on cutting-edge AI technologies and impactful projects.
* A collaborative, innovation-driven work environment.
* Flexible work arrangements and remote work options.
* Continuous learning and professional development support.
Desirable Benefits:
* Health, dental, and vision insurance
* Flexy days off (upto 40)
* Generous paid time off, including vacation and sick leave.
* Stock options and performance-based bonuses.
* Relocation assistance for eligible candidates.
* Access to state-of-the-art AI research labs and computing resources.
* Sponsored attendance at AI/ML conferences and workshops.