1 to 25 of 64 Permanent NumPy Jobs in England

and live trading Requirements: Bachelor's degree or higher in CS, Engineering or other technical discipline Demonstrated ability to program in a scientific computing environment, preferably in Python/NumPy/Pandas and Java/C++ Experience working with distributed systems and large data sets Strong knowledge of algorithms, design patterns, OOP, threading, multiprocessing, etc. Experience with SQL, NoSQL, or More ❯

AI/Data Developer for an urgent contract assignment. Key Requirements: Proven background in AI and data development Strong proficiency in Python , including data-focused libraries such as Pandas, NumPy, and PySpark Hands-on experience with Apache Spark (PySpark preferred) Solid understanding of data management and processing pipelines Experience in algorithm development and graph data structures is advantageous Active SC More ❯

MVP development and iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression 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 ❯

and operational efficiency. Ensure data ethics and preparation are integral to projects. Develop machine learning models and algorithms for complex challenges. Code in R or Python, utilizing libraries like numpy, scipy, and pandas. Conduct exploratory data analysis, model development, and evaluation. Work with both RDBMS and distributed datasets, demonstrating strong SQL skills. Design cloud-based data pipelines for scalable and More ❯

and design principles (SOLID) Excellent understanding of commercial development practices such as testing, documentation, package management and SDLC Excellent understanding of python for numerical programs. In particular, pandas and numpy are a must Excellent problem-solving skills Strong communication skills (the role will involve explaining complex algorithms to colleagues with varying technical and mathematical experience)Desirable Knowledge of UNIX & AWS More ❯

in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work More ❯

in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work More ❯

development 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 More ❯

Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects across More ❯

Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects across More ❯

strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience More ❯

strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience More ❯

strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience More ❯

strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience More ❯

strong interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Practical experience in designing, developing, and maintaining robust data ingestion pipelines. Demonstrated ability to optimize code efficiency, database queries, and system performance. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Practical experience in designing, developing, and maintaining robust data ingestion pipelines. Demonstrated ability to optimize code efficiency, database queries, and system performance. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong More ❯

Role Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. More ❯

of analytics solutions. What you’ll be doing: Designing and building dashboards & automated reporting (Tableau, Power BI). Developing data pipelines, models and analyses using SQL & Python (Pandas/NumPy). Working with cloud environments (AWS Redshift/S3 or similar). Advising business stakeholders on how to use insights to drive measurable impact. Collaborating with experienced data consultants and More ❯

of analytics solutions. What you’ll be doing: Designing and building dashboards & automated reporting (Tableau, Power BI). Developing data pipelines, models and analyses using SQL & Python (Pandas/NumPy). Working with cloud environments (AWS Redshift/S3 or similar). Advising business stakeholders on how to use insights to drive measurable impact. Collaborating with experienced data consultants and More ❯

implement basic AI algorithms and explore practical applications of AI. Overview of AI and Machine Learning Types of machine learning (supervised, unsupervised, reinforcement) Introduction to Python Libraries for AI - NumPy, Pandas, Matplotlib Scikit-learn for machine learning Building AI Models Data preprocessing Training and evaluating models Advanced Programming for AI Integration This programme aims to equip participants with the knowledge 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 ❯

or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency More ❯

Skills & Experience: Essential - Demonstrable experience in Machine Learning, NLP, and GenAI including LLM/SLM fine-tuning and prompt development. Proficiency in Python and data libraries such as Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow. Practical knowledge in SQL/NoSQL databases and API development/integration. Proven ability to analyze model performance and optimize for accuracy, efficiency, and scalability. More ❯