51 to 75 of 127 Pandas Jobs in England

skills. Bonus skills • Experience deploying and managing applications with Azure and Docker. • Familiarity with frameworks like LangChain and Retrieval-Augmented Generation (RAG) models for AI-driven applications. • Experience with pandas for data manipulation. What’s on offer • Regular salary reviews recognising performance and contribution. • Generous annual leave: 25 days plus three days over Christmas. • Flexible hybrid working to support work More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

or 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 More ❯

or 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 More ❯

or 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 More ❯

or 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 More ❯

or 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 More ❯

frameworks Proficiency in analysing and transforming large datasets, with experience in metadata schemas. Knowledge of data pipelines, ingestion processes, and automated categorisation. Proficient in Python (with libraries such as Pandas, NLTK, spaCy) and APIs for AI models. Next Steps: This client will only accept workers operating via an Umbrella or PAYE engagement model. If you are interested in applying for More ❯

a similar role. Strong programming skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn More ❯

joins, CTEs, window functions, optimization techniques) Advanced skills in Microsoft Excel (pivot tables, lookups, data analysis toolpak, macros a plus) Experience writing Python for data manipulation, automation, or visualization (pandas, matplotlib, seaborn) Hands-on experience working with BigQuery or other cloud-based data warehouses (Redshift, Snowflake, etc.) and JSON data structures Strong team player and desire to support work of More ❯

and refining them to strong results. Experienced in engaging with non-technical partners to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with More ❯

Experience delivering data science or data engineering solutions into production. You're comfortable writing production-grade code, not just notebooks. Strong Python and SQL skills, including the basic libraries (Pandas, Numpy, ScikitLearn). You value writing clean, maintainable, and tested code. Proven ability to design, build, and maintain data pipelines and tools from scratch that are reliable, maintainable, and scalable. More ❯

and refining them to strong results. Experienced in engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain More ❯

interoperability between platforms is essential. Programming & Scripting : Knowledge of Python and Rust for pre- and post-processing tasks, prototyping, and interoperability with low-code solutions. Familiarity with MATLAB or Pandas/Polar for numerical computing and data analysis, particularly for processing workflows that require complex calculations. Database Management : Proficiency in SQL for database management (such as Microsoft SQL Server, MySQL More ❯

including Vertex Pipelines (or similar platforms). Technical Proficiency: in SQL and Python, along with familiarity with standard libraries used in data science such as scikit-learn, Keras, TensorFlow, pandas, NumPy, seaborn, and Matplotlib. Desirables: While not essential, the following experience would be highly beneficial: Production Experience with LLM Monitoring: Hands-on experience with monitoring LLMs in production, including familiarity More ❯

Python automation, with 3+ years mentoring/reviewing others. Strong experience in testing, automation frameworks, and quality assurance. Full-stack experience (React, Python, Postgres). Bonus: LLM apps, ETL (Pandas), CI/CD (Git, Jenkins), and data automation. Handle actively welcomes applicants from under-represented backgrounds - we pride ourselves on attracting the best talent for every opportunity through a commitment More ❯

Python automation, with 3+ years mentoring/reviewing others. Strong experience in testing, automation frameworks, and quality assurance. Full-stack experience (React, Python, Postgres). Bonus: LLM apps, ETL (Pandas), CI/CD (Git, Jenkins), and data automation. Handle actively welcomes applicants from under-represented backgrounds - we pride ourselves on attracting the best talent for every opportunity through a commitment More ❯

temporal modeling and deep learning. Document methods and support reproducibility, validation, and publication where appropriate. Essential Requirements Strong programming and modeling skills in Python (NumPy, PyTorch or TensorFlow, SciPy, pandas). In-depth knowledge of machine learning for time-series, including RNNs, LSTMs, GRUs, transformers, attention mechanisms. Solid understanding of probabilistic models (HMMs, Bayesian inference, graphical models). Experience designing More ❯

pipelines and evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

pipelines and evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

or Chatbors, particular voice, is a must-have. Strong recent hands-on capabilities in Python are a must-have. Experience with a microservice environment using tools such as Jupyter, Pandas, Numpy, Fast API, and SQL alchemy is a must. Srong's understanding of deploying and supporting LLM’s in a production environment is a must-have. An interest and understanding More ❯

pipelines and evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks More ❯

quality, documentation, and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

quality, documentation, and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

in Data Analysis, with approx. 4+ years in a senior or equivalent role. Strong experience in SQL (writing and optimising complex queries). Proficiency in Python (including libraries like Pandas, NumPy, SQLAlchemy). Experience working with large datasets , and advanced data modelling techniques. Ability to engage with stakeholders and translate their needs into actionable data solutions. Solid understanding of data More ❯