1 to 25 of 48 Permanent Pandas Jobs in the UK excluding London

years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy, spaCy, PyTorch or TensorFlow). Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real ...

statistical analysis, A/B testing, time-series, regression, classification and optimisation problems. Proficient in SQL & Python. Familiarity with data manipulation libraries (e.g. PySpark, Pandas, Numpy) and machine learning frameworks (e.g. scikit-learn, TensorFlow or PyTorch). Experience with MLOps tools (e.g., MLflow, Databricks Model Registry, Unity Catalog, Vertex ...

their potential impact on products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience building data pipelines and working with structured and unstructured data Solid understanding of SQL and relational and non-relational databases ...

more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and DataOps Experience of IaC tools, particularly Terraform Understanding of implementing ...

more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and DataOps Experience of IaC tools, particularly Terraform Understanding of implementing ...

solutions Broad experience across multiple ML domains, including: Forecasting/Time-Series Modelling Regression Classification Gradient Boosting models (e.g. XGBoost, LightGBM) Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch) Experience with model evaluation, performance monitoring, and accuracy metrics Version control (Git) Experience working with cloud environments (Azure preferred, AWS/ ...

with Computer Vision, Deep Learning, NLP/LLM or Time-Series Analytics solutions. Strong understanding of data analysis and manipulation using tools such as Pandas, NumPy and SQL. Experience deploying AI models into operational environments. Understanding of Responsible AI principles, model explainability and AI security considerations. Experience using ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid understanding ...

years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy). Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real-world business applications. Experience ...

Computer Science, Mathematics, Statistics or another STEM-related discipline. Desirable Skills Experience with cloud platforms such as AWS, Azure or GCP . Experience with Pandas, NumPy and Scikit-learn . Knowledge of data visualisation tools such as Power BI or Tableau. Experience with Git/version control. Exposure to Generative ...

computer vision, machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

analytical approach. Ability to work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review ...

analytical approach. Ability to work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review ...

Strong understanding of core ML concepts - supervised/unsupervised learning, model evaluation, feature engineering - and broad familiarity with common algorithms and architectures. Strong Python (pandas, NumPy, etc.) and SQL skills Comfortable with the standard ML toolkit: Git, Docker, scikit-learn, PyTorch or TensorFlow, and ML pipelines. Hands-on experience with ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem‐solving. Technical Expertise & Tools Python: Advanced, production‐grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem‐solving. Technical Expertise & Tools Python: Advanced, production‐grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

multi-threading (-s), worker processes, memory allocators, compression algorithms, and partitioned database maintenance. Languages & Frameworks: Strong proficiency in Python (including data science stack: Pandas, NumPy, and integration tools like embedPy, PyKX, or qPython). Solid understanding of Java interface programming with KDB+ and platform Familiarity with enterprise messaging middleware (Kafka ...

implementing data science processes. Experience in translating customer requirements into technical requirements and development objectives. Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). Proficient in SQL. Working with unstructured data Building customer ...

implementing data science processes. · Experience in translating customer requirements into technical requirements and development objectives. · Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). · Proficient in SQL. · Working with unstructured data · Building customer ...

production-grade backend systems at scale. Core Technical Skills Strong proficiency in Python as a primary backend language. Hands-on experience with FastAPI and Pandas for building data-driven API services. Solid experience with PostgreSQL - schema design, query optimization, and migrations. Experience with RabbitMQ or similar message brokers for asynchronous ...

champion best practices in MLOps. What You Bring ·Proven experience building and iterating on ML models in a commercial setting. ·Expert-level Python skills (pandas, NumPy, scikit-learn, etc.) and strong statistical grounding. ·Experience working within cloud or modern data environments (Microsoft Fabric, Azure, or Databricks). ·Clear, impactful communication ...

Strong understanding of OOP concepts, design patterns, SOLID principles, algorithms, data structures, and ability to write clean, maintainable code Backend Development – Proficiency in Python (Pandas, FastAPI, Flask) for building enterprise applications, data processing and API development Database Technologies – Hands‐on experience with RDBMS databases (e.g., Oracle, PostgreSQL) and NoSQL databases ...

Strong understanding of OOP concepts, design patterns, SOLID principles, algorithms, data structures, and ability to write clean, maintainable code • Backend Development – Proficiency in Python (Pandas, FastAPI, Flask) for building enterprise applications, data processing, and API development • Frontend Development – Experience with ReactJS , Node.js, TypeScript/JavaScript, and modern web development practices ...

Strong knowledge of modern data science and machine learning techniques, including supervised and unsupervised learning. Proficiency in the Python data science ecosystem (e.g. NumPy, Pandas, scikit-learn, PyTorch, TensorFlow). Experience with big data and distributed analytics platforms (e.g. Spark, Hadoop). Hands-on experience with Natural Language Processing, graph ...