15 of 15 Jupyter Jobs in London

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 ❯

learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python) Ad-hoc data mining for insights using Python + Jupyter notebooks Present insights and predictions in live dashboards using Tableau/PowerBI Lead the presentation of findings to clients through written documentation, calls and presentations Actively seek out new opportunities More ❯

into scalable solutions. Essential Experience & Skills 5+ years' engineering experience, with at least 3 years in ML Ops, Data Engineering, or AI infrastructure. Strong Python engineering skills (Pandas, Numpy, Jupyter, FastAPI, SQLAlchemy). Expertise in AWS services (certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc. More ❯

into scalable solutions. Essential Experience & Skills 5+ years' engineering experience, with at least 3 years in ML Ops, Data Engineering, or AI infrastructure. Strong Python engineering skills (Pandas, Numpy, Jupyter, FastAPI, SQLAlchemy). Expertise in AWS services (certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc. More ❯

cloud platforms (AWS, GCP, Azure). Proficiency in containerization and orchestration (Docker, Kubernetes). Expertise in managing and optimizing cloud-based systems at scale. Preferred Skills Familiarity with Python (Jupyter) and ML frameworks (e.g., PyTorch). Knowledge of monitoring tools (Prometheus, Grafana). Experience with cloud-based databases (RDS, Aurora, Redshift, Cloud SQL, etc.) and visualization tools (QuickSight, Superset). 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 ❯

etc.), state-of-the-art areas (e.g. NLP, Transfer Learning) and modern Deep Learning algorithms (e.g. BERT, LSTM) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit-Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data) Solid understanding of statistics; hypothesis testing, probability distributions, sampling techniques Private Health 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 ❯

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 ❯

/AI/LLM Solutions. A passion for Generative AI, and an understanding of strengths and weaknesses of Generative LLM's and AI technologies. Comfortable working with Python and Jupyter Notebooks. Excellent communication skills - you can toggle seamlessly between presenting to CEOs, and getting in the weeds or white boarding with technical audiences. High tolerance for ambiguity. You can identify More ❯

and dedicated time for your personal development What you'll be working with: •Backend: Distributed, event-driven core Java (90% of the code-base), MySQL, Kafka •Data analytics: Python & Jupyter notebooks, Parquet, Docker •Testing: JUnit, JMH, JCStress, Jenkins, Selenium, many in-house tools •OS: Linux (Fedora for development, Rocky in production) The LMAX way is to use the right tool More ❯

power dashboards and applications You'll integrate third-party APIs and databases into our data flows You'll perform in-depth analysis and data transformations with SQL, Python, and Jupyter Notebooks You'll prototype internal data applications and tools (Streamlit, Jupyter) You'll ensure data quality and reliability throughout the lifecycle You'll collaborate with product, technology, and strategy teams … to visualisation and presentation. Tool Building: Passion for creating robust and usable tools to enhance team efficiency. Data Analysis Skills: Proficiency in SQL, python, pandas/numpy, Databricks/Jupyter Notebooks, and experience with large datasets in production environments. Curiosity and Drive: Self-motivated with a strong desire to learn and improve without lots of help and support. Growth mindset … is an excellent start What We Work With dbt for data modelling Databricks Delta Lake for data lake and warehouse storage and querying Python as our main programming language Jupyter and Jupyter Hub for notebook analytics and collaboration Circle CI for continuous deployment AWS cloud infrastructure Kubernetes for data services and task orchestration Google Analytics, Amplitude and Firebase for client 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 ❯