Senior Data Scientist

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-growingbiotech companyrevolutionizingprecision medicineandbiomedical research. Our client leveragesadvanced data scienceandmachine learningto acceleratedrug discovery,optimise patient outcomes, anduncover breakthroughsin disease understanding. Backed bytop-tier healthcare investors, they collaborate withleading researchers, clinicians, and pharmaceutical companiesto drive data-powered healthcare innovation.

We’re seeking a passionateSenior Data Scientistto join the team and contribute to life-changing research and development initiatives. You’ll work cross-functionally withclinical experts, geneticists, and AI specialiststo build cutting-edge data models and derive actionable insights frommulti-modal biomedical datasets— fromgenomics and clinical trialstopatient recordsandreal-world evidence.

Key Responsibilities:

• Develop and deploy predictive modelsfor drug discovery, disease progression analysis, and personalized medicine strategies.
• Analyze complex biological, clinical, and genomic datasetsto uncover insights that improve diagnostics, treatments, and patient care.
• Build and optimize machine learning pipelinesfor feature engineering, model training, and validation at scale.
• Work with domain expertsto 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 scientistsand 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 statisticsor causal inference methods.
• Experience with federated learningorprivacy-preserving data science(helpful for multi-institution data collaboration).
• Knowledge of regulatory frameworkslikeGDPR,HIPAA, orMHRAcompliance for healthcare data.
• Software engineering best practices— CI/CD pipelines, version control (Git), Docker, or Kubernetes.
• Experience with biological pathway analysisorgenetic 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.