12 of 12 DemandTrendPermanent Jupyter Jobs in the UK

experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Strong skills in data preprocessing, wrangling, and augmentation techniques Experience deploying scalable AI solutions on cloud platforms (AWS More ❯

knowledge of React (not a frontend role, but an understanding of the stack is important) Hands-on experience with containerisation (Docker) and cloud deployment (Terraform, microservices, Azure) Exposure to Jupyter notebooks , and understanding of how machine learning models are developed and deployed Experience in fast-paced or start-up environments where you’ve contributed across the stack Background & Education Degree More ❯

knowledge of React (not a frontend role, but an understanding of the stack is important) Hands-on experience with containerisation (Docker) and cloud deployment (Terraform, microservices, Azure) Exposure to Jupyter notebooks , and understanding of how machine learning models are developed and deployed Experience in fast-paced or start-up environments where you’ve contributed across the stack Background & Education Degree More ❯

knowledge of React (not a frontend role, but an understanding of the stack is important) Hands-on experience with containerisation (Docker) and cloud deployment (Terraform, microservices, Azure) Exposure to Jupyter notebooks , and understanding of how machine learning models are developed and deployed Experience in fast-paced or start-up environments where you’ve contributed across the stack Background & Education Degree More ❯

knowledge of React (not a frontend role, but an understanding of the stack is important) Hands-on experience with containerisation (Docker) and cloud deployment (Terraform, microservices, Azure) Exposure to Jupyter notebooks , and understanding of how machine learning models are developed and deployed Experience in fast-paced or start-up environments where you’ve contributed across the stack Background & Education Degree More ❯

knowledge of React (not a frontend role, but an understanding of the stack is important) Hands-on experience with containerisation (Docker) and cloud deployment (Terraform, microservices, Azure) Exposure to Jupyter notebooks , and understanding of how machine learning models are developed and deployed Experience in fast-paced or start-up environments where you’ve contributed across the stack Background & Education Degree More ❯

Python) Start-up/Scale-up Experience Strong cloud skills (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Experience in automating deployments and orchestrating cloud environments Nice to have: Python (Jupyter, PyTorch), monitoring tools (Prometheus, Grafana), cloud databases (RDS, Aurora, Spanner), CI/CD tools (CircleCI), and data visualisation experience. This is a unique opportunity to join a visionary team redefining More ❯

and evaluate highly innovative models for Natural Language Programming (NLP), Large Language Model (LLM), or Large Computer Vision projects. -Use SQL to query and analyze the data. -Use Python, Jupyter notebook, and Pytorch to train/test/deploy ML models. -Use machine learning and analytical techniques to create scalable solutions for business problems. -Research and implement novel machine learning More ❯

include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series More ❯

certifications Azure Synapse: Synapse-link, on-demand SQL engine, dedicated SQL pool Writing unit tests, git Version control Awareness of reliability patterns in ETL pipelines Use of python in Jupyter notebooks for data processing Azure storage technologies and cost/performance characteristics Power BI, DAX, data flows Techniques and tools for sanitizing data prior to use Awareness of Kimball modelling More ❯

be eligible for SC Clearance A strong understanding of secure data practices in government or similarly regulated environments Practical experience building and managing Python-based analytical tooling environments (e.g. JupyterHub, VS Code in-browser) Demonstrable experience developing end-to-end data pipelines, including ingestion, transformation, validation, and output layers Familiarity with best practices in CI/CD, infrastructure-as-code More ❯

scripts and visualizations to explore and summarize biological experiment data. Apply statistical techniques (e.g. descriptive statistics, t-tests, ANOVA, regression) to help interpret experiments Create reproducible analysis workflows using Jupyter, Python, and associated libraries. Work with scientists to understand experimental goals and tailor analyses accordingly. Document analyses and communicate findings in a clear, concise manner. Collaborate with the data engineering … statistics: distributions, hypothesis testing, confidence intervals, regression. Experience working with structured datasets Ability to produce clear, well-commented code and visual outputs (e.g. plots, dashboards). Comfortable working in Jupyter Notebooks and collaborating with experimental teams. A degree (BSc or MSc) in a quantitative field such as Biology, Bioinformatics, Statistics, Data Science, or related discipline. There is an excellent salary More ❯