151 to 175 of 216 Permanent NumPy Jobs

setting? Were looking for a talented OPS Engineer to join our growing teams in Erskine or Newcastle. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines More ❯

and non-technical stakeholders. Stay ahead of the curve by experimenting with emerging AI and ML techniques. What You’ll Bring Strong background in Python or R (e.g., Pandas, NumPy, Scikit-learn, TensorFlow). Skilled in SQL and statistical analysis. Proven experience in data science, ideally within energy, optimisation, or IoT-focused applications. Solid grasp of machine learning techniques such More ❯

load data in various data stores like RDBMS, Oracle, S3, PL/SQL, and/or shared drives. 9. Solid experience in Python and libraries such as Panda/NumPy, etc. or Spark 10. Demonstrable experience developing scripting in Linux and Windows 11. Experience with migrating applications to AWS (Cloud) will be an added advantage 12. Knowledge of Cloud computing More ❯

Google Analytics, conversion optimisation Skills & Experience Essential Strong SQL proficiency for data extraction and transformation Advanced Excel (pivot tables, VLOOKUPs, formulas) Power BI or Tableau experience Python familiarity (pandas, numpy) Proven data or BI role background Experience with large, complex datasets History of delivering practical insights Strong communication skills Desirable Wholesale/distribution/supply chain experience ERP systems exposure More ❯

production-grade analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/ More ❯

production-grade analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/ More ❯

ArcGIS), remote sensing techniques, and the application of data science in the IC. Expert proficiency in Python (or similar languages) and experience with data science libraries (TensorFlow, PyTorch, Pandas, NumPy). Strong experience with big data processing tools (e.g., Spark, Hadoop, AWS or Azure cloud platforms). Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS) and More ❯

building and orchestrating ML models for Computer Vision tasks Technical Stack : You are highly proficient in Python and expert in relevant ML frameworks (PyTorch, TensorFlow/Keras) and packages (NumPy, Pandas) Data Skills : Preferably, you have hands on experience with data science tooling and expertise in dataset curation, analysis, and cleaning for ML training Code Quality : You write high quality More ❯

or MATLAB. Understanding of Convolutional Neural Networks (CNNs) and Feature Extraction techniques. Basic knowledge of programming languages including Python, C++, and C, along and libraries such as Scikit-Learn, NumPy, and/or SciPy . Your Package & Perks: A competitive salary Flexible working hours 32 days holiday, (including public Holidays) plus the opportunity to earn up to an extra More ❯

or MATLAB. Understanding of Convolutional Neural Networks (CNNs) and Feature Extraction techniques. Basic knowledge of programming languages including Python, C++, and C, along and libraries such as Scikit-Learn, NumPy, and/or SciPy . Your Package & Perks: A competitive salary Flexible working hours 32 days holiday, (including public Holidays) plus the opportunity to earn up to an extra More ❯

learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building More ❯

learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building More ❯

learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building More ❯

ready using methodologies. Python Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise More ❯

learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building More ❯

related technical discipline. Good knowledge of machine learning and computer vision algorithms. Familiarity with real-time imaging pipelines. Experience with scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit's, etc. Experience in standard software engineering practices including version control systems and software testing methodologies. Excellent oral and written communication skills. Analytical thinker, attentive to details, creative and More ❯

is not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such More ❯

is not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such More ❯

paced and data-rich environment. You’ll need: 2–5+ years’ experience in data science or ML (not a graduate role; sports background a plus) Strong Python skills (pandas, numpy, scikit-learn, etc.) Hands-on experience with tree-based algorithms (XGBoost, LightGBM) and other ML methods Solid grasp of statistics, probability, and applied maths Proficiency in SQL , familiarity with NoSQL More ❯

paced and data-rich environment. You’ll need: 2–5+ years’ experience in data science or ML (not a graduate role; sports background a plus) Strong Python skills (pandas, numpy, scikit-learn, etc.) Hands-on experience with tree-based algorithms (XGBoost, LightGBM) and other ML methods Solid grasp of statistics, probability, and applied maths Proficiency in SQL , familiarity with NoSQL More ❯

the latest LLM and ML research. What We’re Looking For MSc or PhD in Computer Science, Data Science, Mathematics, Physics, or a related field. Strong Python skills (pandas, NumPy, scikit-learn, PyTorch). Curiosity, rigour, and drive to improve model performance. Why Join Us Work on real applied LLMs from training to deployment. Collaborate with an ambitious, research-informed More ❯

Skills & Experience 6+ years’ experience in Data Science. Demonstrated experience in technical consulting, ideally with exposure to public sector. Strong proficiency in Python and key data science libraries (pandas, NumPy, scikit-learn, PyTorch/TensorFlow). Broad, practical understanding of machine learning and AI methodologies. Proven success in proof-of-concept design and delivery. Strong technical leadership and mentoring skills. More ❯

Skills & Experience 6+ years’ experience in Data Science. Demonstrated experience in technical consulting, ideally with exposure to public sector. Strong proficiency in Python and key data science libraries (pandas, NumPy, scikit-learn, PyTorch/TensorFlow). Broad, practical understanding of machine learning and AI methodologies. Proven success in proof-of-concept design and delivery. Strong technical leadership and mentoring skills. More ❯

Master’s degree (or higher) Data Science, Computer Science, Mathematics, Statistics, Physics, or Economics Strong academic background – ideally from a Redbrick or Russell Group university Proficient in Python (pandas, NumPy, scikit-learn, etc.) and SQL Solid understanding of machine learning concepts and statistical analysis Strong problem-solving and critical thinking skills Excellent communication and presentation abilities What’s on offer More ❯

Master’s degree (or higher) Data Science, Computer Science, Mathematics, Statistics, Physics, or Economics Strong academic background – ideally from a Redbrick or Russell Group university Proficient in Python (pandas, NumPy, scikit-learn, etc.) and SQL Solid understanding of machine learning concepts and statistical analysis Strong problem-solving and critical thinking skills Excellent communication and presentation abilities What’s on offer More ❯