16 of 16 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 ❯

working as a Data Scientist or Machine Learning Engineer in a commercial setting. Strong programming skills in Python, with hands-on experience using libraries such as Pandas, Scikit-Learn, Jupyter, and Matplotlib. Proficient in SQL for data extraction and transformation. Experience with Google Cloud Platform (GCP) and Vertex AI for developing and deploying ML services is highly desirable. Solid understanding 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

cutting-edge ML technology across the business. Machine Learning Engineer, key skills: Significant experience working as a Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and More ❯

applying threat and data modeling, advanced data correlation, and statistical analysis to develop alerts, notable events, investigative dashboards, and metrics-driven reports. Familiarity with scripting (e.g., Python, PowerShell) and Jupyter Notebooks for basic automation of security analysis tasks Experience as a Threat Researcher and/or Intelligence Analyst. Being You Diversity is a whole lot more than what we look More ❯

Work with the Senior Engineer/Tech Lead to implement and optimise data pipelines and ML models. Develop high-quality, maintainable code in Python and PySpark. Use SQL and Jupyter to analyse, transform and validate data for ML use cases. Operate in a cloud environment (AWS/Azure - moving towards Azure). Collaborate with stakeholders and technical teams to deliver … solutions that support business growth. Skills & Experience Required: Strong hands-on experience in Python, PySpark, SQL, Jupyter . Experience in Machine Learning engineering or data-focused development. Exposure to working in cloud platforms (AWS/Azure) . Ability to collaborate effectively with senior engineers, data scientists, and architects. Proactive, detail-oriented, and eager to contribute within a greenfield project environment. More ❯