10 of 10 Jupyter Jobs in London

understanding of strengths and weaknesses of Generative LLM's • Fundamental knowledge of ML, and basic knowledge of AI, NLP, and Large Language Models (LLM) • Comfortable working with Python and Jupyter Notebooks • Should have in-depth knowledge and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills – Good to have: • Expertise in 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 ❯

with our data, so you will need to understand how to develop your own models Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter Previous experience in finance is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here. Why should you apply? Highly More ❯

findings and recommendations to non-technical stakeholders 3. Ideal Qualifications 5+ years of applied data science or analytics experience in business settings Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills Experience with data visualization tools (e.g., Tableau, Power BI) Solid understanding of statistical modeling, experimentation, and A/B testing Strong communication skills for translating technical More ❯

production. Requirements: Experience in a client-facing technical role (Solutions Engineer, AI Consultant, or similar) Strong Python skills and experience with LLMs/LangChain Confident building quick prototypes (Streamlit, Jupyter, etc.) Able to bridge business needs and technical delivery Startup mindset: fast-moving, collaborative, hands-on Bonus: experience in finance, legal, or insurance; Azure exposure; ISO 27001 familiarity This is More ❯

Python data libraries (Pandas, NumPy) (preferably) from the Trading world. They also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine learning libraries like PyTorch, XGBoost and JAX Understanding of crypto or traditional financial markets Strong API design and documentation skills What do you get in return More ❯

Python data libraries (Pandas, NumPy) (preferably) from the Trading world. They also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine learning libraries like PyTorch, XGBoost and JAX Understanding of crypto or traditional financial markets Strong API design and documentation skills What do you get in return More ❯

as designing experiments, gathering and preprocessing data, building and evaluating models, and collaborating closely with engineering teams to deploy production‐ready solutions. Ideal candidates should be proficient in Python (Jupyter Notebooks), familiar with machine learning frameworks like TensorFlow or PyTorch, and experienced in analyzing large datasets and building predictive models. In addition, you will write, review, and validate prompt‐based … train AI systems. You are a good fit if you: Have over 3+ years of professional experience in data science or applied analytics. Are highly skilled in Python and Jupyter notebooks. Have experience using libraries including numpy, pandas, scipy, sympy, scikit-learn, torch, tensorflow. Have a bachelor's degree in data science, statistics, computer science, or related field in the More ❯

Data Scientist - Remote (Data Scientist, Data Science, Data Analyst, Data Analysis, ETL pipeline, Jupyter notebooks, Python, Azure Data Factory, Cosmos DB, PostgreSQL, QGIS, PostGIS, Statistics, Data Analytics, C# .NET, Data Scientist, Data Science, Data Analyst, Data Analysis) Our client is a prestigious technology company who focus in the Insurance market. They have been a market leader for many years and … part in data visualization, statistical analysis and collaboration with cross-functional teams to implement data-driven decision making. We are seeking a Data Scientist with experience of Python and Jupyter notebooks with the capability to source data and communicate and liaise with data providers. You will need an understanding of data licensing and its implications, full ETL pipeline experience and … full data lifecycle management knowledge. Essential skills include Jupyter notebooks and Python, strong Data Visualization and presentation, expertise in Data Science and Data Analysis and proficiency in Statistics and Data Analytics. Knowledge of Azure Data Factory, Cosmos DB, PostgreSQL, QGIS/PostGIS and C#.NET is highly desirable, as is any experience in the Insurance industry. Excellent problem-solving and analytical More ❯

research/production use. Scale up and productionize research model pipelines into large-scale, reliable distributed compute jobs. Manage distributed compute workflows with Dask, Ray, and other frameworks. Develop Jupyter tooling, templates, and widgets for strategy prototyping and parameter tuning. Implement performance attribution, PnL decomposition, and diagnostic tools. Build dashboards and visualizations (Bokeh, Matplotlib) for order book and strategy monitoring. … development experience. Extremely effective in writing clean, modern Python code. Experience building and documenting high-quality APIs for developers. Deep Python ecosystem expertise: Pandas, Numpy, Bokeh, PyArrow, matplotlib, IPyWidgets, Jupyter, uv, etc. Proven experience building large data pipelines/ETL workflows. Comfortable working in Jupyter notebooks. An understanding of crypto or TradFi markets and trading concepts. Nice to Have Experience More ❯