1 to 25 of 51 Permanent NumPy Jobs in the South East

efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity with More ❯

efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity with More ❯

efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity with More ❯

Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/ More ❯

Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/ More ❯

Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/ More ❯

a plus) Solid understanding of software architecture, algorithms, data structures and computer science fundamentals Interest or experience in quant finance Advanced knowledge of the python data science stack (Pandas, NumPy, SciPy) is a plus Strong academic background from a top tier university a major plus If this sounds of interest we'd love to hear from you! Vertex Search is More ❯

a plus) Solid understanding of software architecture, algorithms, data structures and computer science fundamentals Interest or experience in quant finance Advanced knowledge of the python data science stack (Pandas, NumPy, SciPy) is a plus Strong academic background from a top tier university a major plus If this sounds of interest we'd love to hear from you! Vertex Search is More ❯

a plus) Solid understanding of software architecture, algorithms, data structures and computer science fundamentals Interest or experience in quant finance Advanced knowledge of the python data science stack (Pandas, NumPy, SciPy) is a plus Strong academic background from a top tier university a major plus If this sounds of interest we'd love to hear from you! Vertex Search is More ❯

asynchronous programming, and performance optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working with More ❯

asynchronous programming, and performance optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working with More ❯

asynchronous programming, and performance optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working with More ❯

. Experience in applying statistical and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin-client More ❯

. Experience in applying statistical and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin-client More ❯

in production. What We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯

in production. What We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯

lead technical workstreams to elevate team capability. Essential Skills & Experience Proven experience in analytics engineering , data engineering , or model development roles. Advanced proficiency in Python (including libraries such as NumPy and Pandas) and SQL . Demonstrated ability to deliver production-ready solutions in a commercial environment. Strong communication skills with the ability to engage stakeholders and translate technical work into More ❯

real-time and batch data pipelines. Required Qualifications A degree in Computer Science, Engineering, Mathematics, Physics, or a related STEM field. Strong proficiency in Python (including libraries like pandas, numpy, etc.). Solid experience with SQL and working with large datasets. Familiarity with Git, CI/CD workflows, and Docker. Hands-on experience with at least one cloud platform (AWS More ❯

real-time and batch data pipelines. Required Qualifications A degree in Computer Science, Engineering, Mathematics, Physics, or a related STEM field. Strong proficiency in Python (including libraries like pandas, numpy, etc.). Solid experience with SQL and working with large datasets. Familiarity with Git, CI/CD workflows, and Docker. Hands-on experience with at least one cloud platform (AWS More ❯

real-time and batch data pipelines. Required Qualifications A degree in Computer Science, Engineering, Mathematics, Physics, or a related STEM field. Strong proficiency in Python (including libraries like pandas, numpy, etc.). Solid experience with SQL and working with large datasets. Familiarity with Git, CI/CD workflows, and Docker. Hands-on experience with at least one cloud platform (AWS More ❯

Communicate technical concepts clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication More ❯

A recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A More ❯

A recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A More ❯

A recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A More ❯

similar domains with forecasting needs. Skills and competencies Essential: Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. More ❯