11 of 11 Permanent Jupyter Jobs in London

to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real-World Experience : Work on live AI projects with real business More ❯

learn Solid understanding of ML workflows: data cleaning, model development, tuning, evaluation Familiar with model deployment, API development, or real-world ML integration Experience with tools like Google Colab, Jupyter, and cloud ML platforms Strong analytical, problem-solving, and communication skills Must be based in the UK and open to remote collaboration across time zones Nice to Have Experience with 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 ❯

best practices . Apply modern software engineering standards including testing, version control, and CI/CD pipelines. Key Skills: Proven experience in Python programming for data analysis (pandas, numpy, Jupyter). Strong object-oriented programming and design pattern knowledge. Experience with SQL and relational databases. Familiarity with data visualisation tools (e.g., Plotly Dash, Power BI). Understanding of software development More ❯

best practices . Apply modern software engineering standards including testing, version control, and CI/CD pipelines. Key Skills: Proven experience in Python programming for data analysis (pandas, numpy, Jupyter). Strong object-oriented programming and design pattern knowledge. Experience with SQL and relational databases. Familiarity with data visualisation tools (e.g., Plotly Dash, Power BI). Understanding of software development More ❯

for automation. Hands-on experience with containerization & orchestration (Docker, Kubernetes, Terraform). Skilled in cloud platforms (AWS, GCP, or Azure). Bonus points for: Familiarity with ML frameworks (PyTorch, Jupyter). Knowledge of cloud monitoring tools (Prometheus, Grafana). Experience with cloud-based databases (RDS, Aurora, Redshift, Spanner, etc.). Exposure to CI/CD pipelines (e.g., CircleCI). What 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 ❯

one major cloud platform (AWS, GCP, or Azure). Experience with containerization and orchestration (Docker, Kubernetes). Ability to manage and optimize large-scale cloud infrastructure. Familiarity with Python (Jupyter) and ML frameworks (e.g., PyTorch). Experience with cloud monitoring tools (Prometheus, Grafana). Exposure to cloud-based databases (RDS, Aurora, Spanner, etc.) and data-visualisation tools. Knowledge of CI More ❯

one major cloud platform (AWS, GCP, or Azure). Experience with containerization and orchestration (Docker, Kubernetes). Ability to manage and optimize large-scale cloud infrastructure. Familiarity with Python (Jupyter) and ML frameworks (e.g., PyTorch). Experience with cloud monitoring tools (Prometheus, Grafana). Exposure to cloud-based databases (RDS, Aurora, Spanner, etc.) and data-visualisation tools. Knowledge of CI More ❯

SQL and Python Apply statistical techniques (segmentation, regression, predictive modelling) Partner with stakeholders to translate business questions into data-driven answers About You Strong experience with SQL and Python (Jupyter Notebooks) Solid grounding in statistical analysis and forecasting methods Commercially minded - able to connect technical outputs to business goals Excellent communicator, proactive and adaptable to a fast-paced environment Comfortable More ❯

SQL and Python Apply statistical techniques (segmentation, regression, predictive modelling) Partner with stakeholders to translate business questions into data-driven answers About You Strong experience with SQL and Python (Jupyter Notebooks) Solid grounding in statistical analysis and forecasting methods Commercially minded - able to connect technical outputs to business goals Excellent communicator, proactive and adaptable to a fast-paced environment Comfortable More ❯