Job Description
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 withstructured/unstructureddata.
- 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.
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