151 to 175 of 183 NumPy Jobs in England

to gain a deep understanding of quant trading while leveraging your technical expertise to drive results. What you'll bring 2+ years professional experience in Python, including use of NumPy and other scientific libraries. A passion for working with data/dataframes and solving data-related challenges. Strong Pandas experience is required. Minimum bachelors degree in a STEM subject at More ❯

to gain a deep understanding of quant trading while leveraging your technical expertise to drive results. What you'll bring 2+ years professional experience in Python, including use of NumPy and other scientific libraries. A passion for working with data/dataframes and solving data-related challenges. Strong Pandas experience is required. Minimum bachelors degree in a STEM subject at More ❯

to gain a deep understanding of quant trading while leveraging your technical expertise to drive results. What you'll bring 2+ years professional experience in Python, including use of NumPy and other scientific libraries. A passion for working with data/dataframes and solving data-related challenges. Strong Pandas experience is required. Minimum bachelors degree in a STEM subject at More ❯

Experience Current enhanced DV clearance (mandatory) Proven experience in a data science or machine learning role Strong programming skills in Python and familiarity with key data libraries (e.g. pandas, NumPy, scikit-learn) Experience with data wrangling , feature engineering, and model optimisation Understanding of data pipelines , APIs, and production deployment workflows Excellent communication skills and a collaborative approach Why Apply? Work More ❯

and concise business narratives Contributing to simple, reliable data pipelines and automated quality checks About You Minimum 1 year of commercial Data Science experience Strong hands-on Python (pandas, NumPy, scikit-learn) and SQL Sound understanding of statistics and forecasting Confident communicator - able to explain technical work clearly to non-technical audiences Why Apply Opportunity to build from scratch within More ❯

Experience Current enhanced DV clearance (mandatory) Proven experience in a data science or machine learning role Strong programming skills in Python and familiarity with key data libraries (e.g. pandas, NumPy, scikit-learn) Experience with data wrangling , feature engineering, and model optimisation Understanding of data pipelines , APIs, and production deployment workflows Excellent communication skills and a collaborative approach Why Apply? Work More ❯

solution across the business units through architecting, positioning and delivering data science and machine learning. Key Skills: Machine Learning, deep learning TensorFlow & NLP (Natural Language Processing) Python - Pandas, PyCharm, Numpy SQL - MySQL, PostgreSQL, NoSQL, RDBMS Design and modelling GitHub & Jenkins Data Modelling, Data Wrangling and Extraction *Hybrid working, 2 days per week in Sheffield Office* Job Title: Ai Engineer Location More ❯

data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch More ❯

you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn 🧩 Understanding of machine learning algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and More ❯

data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch More ❯

you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn 🧩 Understanding of machine learning algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and More ❯

you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn 🧩 Understanding of machine learning algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and More ❯

data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch More ❯

data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch More ❯

data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch More ❯

you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn 🧩 Understanding of machine learning algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and More ❯

you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn 🧩 Understanding of machine learning algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and More ❯

Scientist, your background will 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 More ❯

and graph analytics and hands-on experience and solid understanding of machine learning and deep learning methods Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Preferred Qualifications, Capabilities, and More ❯

ideas with the wider team, learn from and contribute to the body of knowledge. Key Skills Experience using Python and SQL. Strong proficiency with data manipulation including packages like NumPy, Pandas. Knowledge of machine learning techniques and their respective pros and cons. Confident communicator and contributes effectively within a team environment. Self driven and willing to lead on projects/ More ❯

Science with reasonable industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big data More ❯

fundamentals in software engineering: testing, version control, CI/CD, clean architecture Passion for building internal tools, research frameworks, or working on data-heavy systems Bonus: Exposure to pandas, NumPy, asyncio, Cython, or PyArrow. Familiarity with C++ is a plus Bonus++: Experience working with quants, data scientists, or in trading environments Tech Stack: Python 3.11+ (fast, modern, typed) Dask, pandas … PyArrow, NumPy PostgreSQL, Parquet, S3 Airflow, Docker, Kubernetes, GitLab CI Internal frameworks built for scale and speed Why Join: Engineers own projects end-to-end—from design to deployment to impact Work side-by-side with quants, traders, and researchers in a flat, fast-moving team Competitive compensation at the top of the market, with research-aligned bonuses No bureaucracy. More ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's … Machine Learning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push More ❯

scalable, and maintainable applications using Python and Azure cloud technologies for commodities trading solutions. Leverage strong proficiency in Python, including use of numerical and scientific libraries such as Pandas, NumPy, SciPy etc. Utilize a second strongly typed programming language (e.g., C#, C++, Rust, or Java) as needed. Implement application architecture and DevOps best practices, including Infrastructure as code, Kubernetes, Docker … into technical specifications and software products. Mandatory Skills Extensive experience in Python application development, especially within trading, finance, or quantitative domains. Proficiency with major Python numerical libraries (e.g., pandas, numpy, scipy, stats). Experience with at least one additional strongly typed programming language (C#, C++, Rust, Java, etc.). Strong background in Azure cloud application development, including security, observability, storage More ❯

hear from you if you Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience productionising machine learning models Are an expert in one of predictive modeling, classification, regression, optimisation or recommendation systems Have experience with Spark Have knowledge of … Models (fine tuning, RAG, agents) Experience with graph technology and/or algorithms, understanding of NLP algorithms Our technology stack Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOp/DevOps: Terraform, Docker, Airflow, MLFlow, NewRelic The interview process Recruiter Call (30 minutes) Meeting a Machine More ❯