Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & featureengineering * Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies * Some knowledge of containerisation & use of tools like Docker & Docker Compose Nice More ❯
Cambridge, Cambridgeshire, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
datasets (e.g. genomic sequences, patient records, imaging) Collaborate with bioinformaticians and clinical researchers to translate data into actionable insights Contribute to the development of internal tools for data preprocessing , featureengineering , and model evaluation Requirements: 3+ years of experience in data science or ML, ideally in biotech or healthcare Strong Python programming skills and experience with ML libraries More ❯
environment (AWS, GCP or Azure) Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and featureengineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring Contribute to documentation, knowledge sharing More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
BDO
production-level solutions Troubleshoot and debug code Work with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and featureengineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning Deployment: Familiarity with containerised deployment More ❯