1 to 25 of 53 Permanent Pandas Jobs in the UK excluding London

These are ourvaluesand influence everything we do. Preferred Qualifications Familiarity building scalable services in a microservices architecture. Familiarity with statistical tools such as SAS, or Python (with NumPy, SciPy, Pandas) Familiarity with public cloud platforms, such as AWS, Azure, or GCP. Strong testing automation experience, preferably in unit frameworks Diverse and Inclusive At SAS, it's not about fitting into More ❯

highly numerate subject (e.g. computer science, engineering, mathematics, or data science). Minimum 2 years' experience in Python development, including use of scientific and data libraries such as NumPy, pandas, SciPy, or PySpark. Experience working with machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, or similar. Strong grasp of object-oriented software engineering principles, with a focus More ❯

highly numerate subject (e.g. computer science, engineering, mathematics, or data science). Minimum 2 years' experience in Python development, including use of scientific and data libraries such as NumPy, pandas, SciPy, or PySpark. Experience working with machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, or similar. Strong grasp of object-oriented software engineering principles, with a focus More ❯

Data Scientist - Hybrid (Bristol-based) £40,000 - £45,000 (up to £50,000 for exceptional candidates) Hybrid Working | Python & Pandas Are you passionate about data and ready to make a real impact in the world of cyber risk? We're working with a forward-thinking company that's pioneering cyber risk modelling using advanced stochastic techniques, and they're on … and process efficiency. The work you do will directly influence insights into cyber exposure and risk trends. Key Responsibilities Clean, validate, and standardise large insurance datasets using Python (especially Pandas) Develop and refine internal tools and utilities for data cleaning workflows Support the integration of LLMs to automate data prep, including prompt engineering and model evaluation Generate insightful data reports … data science, reinsurance, and cyber risk What We're Looking For 2-4 years in a data-driven or technical role Strong Python skills with a deep understanding of Pandas Excellent attention to detail and a strong sense of data quality Commercial experience blending data engineering and data science approaches Experience with data ingestion and ETL pipelines Curious, adaptable, and More ❯

under time pressure—while continuously refining and improving the systems over time. Essential • 2:1 degree in computer science or relevant engineering discipline• Python/C C, PyTorch, Numpy, Pandas, Tensorflow, Computer Vision, OpenCV, JavaScript, HTML• Solution orientated with an ability to think outside the box Desirable experience • Hands-on experience designing and implementing control mechanisms for production line automation More ❯

Essential 2:1 degree in computer science or relevant engineering discipline 5+ year Software Engineering lead experience, including system architect, mentoring, and code reviews Python/C++, PyTorch, Numpy, Pandas, Tensorflow, Computer Vision, OpenCV, JavaScript, HTML Hands-on experience designing and implementing control mechanisms for production line automation Solution orientated with an ability to think outside the box Desirable experience More ❯

software development, including data acquisition and/or data analysis. (S&I) Experience developing well-designed, robust software in Python and its scientific packages (such as numpy, scipy, matplotlib, pandas). (S&I) Understanding of modern software development practices (e.g. testing, version control, continuous integration, Agile, object-oriented design). (S&I) Experience of leading software projects through the full More ❯

functional teams to enhance testing practices across cloud-native microservices and data platforms. You'll develop scalable test automation frameworks with a focus on data validation using tools like Pandas, and lead strategies for testing data lakes. Collaborate closely with QA and Java/Spring Boot development teams to ensure data quality and reliability across our sports technology ecosystem. What … Your Day Will Look Like Build scalable and robust frameworks for validating complex data systems, pipelines, and APIs using tools like Pandas, Great Expectations, and Java modules. Collaborate with development teams to design and implement automated tests for microservices, emphasizing Spring Boot and Java-based architectures. Implement testing strategies for AWS data lakes (e.g., S3, Glue, Athena) with a focus … methodologies and train teams to independently implement and use the automation frameworks. Skills, Knowledge, and Expertise Expertise in validating complex datasets, creating synthetic test data, and leveraging tools like Pandas and Python for comprehensive data quality assurance. Proven ability to build and maintain scalable test automation frameworks, with a focus on backend, API, and data systems using tools like Pytest More ❯

functional teams to enhance testing practices across cloud-native microservices and data platforms. You'll develop scalable test automation frameworks with a focus on data validation using tools like Pandas, and lead strategies for testing data lakes. Collaborate closely with QA and Java/Spring Boot development teams to ensure data quality and reliability across our sports technology ecosystem. What … Your Day Will Look Like Build scalable and robust frameworks for validating complex data systems, pipelines, and APIs using tools like Pandas, Great Expectations, and Java modules. Collaborate with development teams to design and implement automated tests for microservices, emphasizing Spring Boot and Java-based architectures. Implement testing strategies for AWS data lakes (e.g., S3, Glue, Athena) with a focus … methodologies and train teams to independently implement and use the automation frameworks. Skills, Knowledge, and Expertise Expertise in validating complex datasets, creating synthetic test data, and leveraging tools like Pandas and Python for comprehensive data quality assurance. Proven ability to build and maintain scalable test automation frameworks, with a focus on backend, API, and data systems using tools like Pytest More ❯

Processing team. Join a small, ambitious team working closely with Java and Data Science teams to build and support infrastructure for Credit Risk Management, using technologies like FastAPI, Pandera, Pandas, and Pydantic. The role involves collaboration, architecture development, code review, and supporting data science infrastructure. Remote work is possible with occasional office visits; based anywhere in the UK with the More ❯

experience with Python and frameworks like Django/Flask/FastAPI. Database Expertise: Proficient with relational (PostgreSQL, MySQL) and NoSQL (MongoDB) databases. Data Analysis Skills: Experience using libraries like Pandas and NumPy. Software Development Best Practices: Understands object-oriented programming, Agile/Scrum methodologies, and version control (e.g., GitHub). Problem-Solving & Analytical Abilities: Demonstrated ability to solve complex problems More ❯

model performance evaluation, hyperparameter tuning, and maintenance using tools like Vertex AI Pipelines. Cloud Computing (Google Cloud Platform - GCP Preferred) Technical Expertise & Tools Python: Advanced proficiency in data analysis (Pandas, NumPy), machine learning, PI development (Flask/FastAPI), and writing clean, maintainable code. SQL: Expertise in querying, database design/optimization, stored procedures, functions, partitioning/clustering strategies for BigQuery More ❯

familiarity with LLM/GenAI prompting and augmentation for textual analysis, with an interest in learning more. Experience working with commonly used data science libraries and frameworks, e.g. Spacy, pandas, numpy, scikit-learn, Keras/TensorFlow, PyTorch, LangChain, Huggingface transformers etc. Familiar with both on-premises and cloud-based platforms (e.g. AWS). Working understanding of ML Ops workflows and More ❯

some of the biggest names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience More ❯

some of the biggest names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience More ❯

fresh ideas to the team. Skills and Experience: Degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proficiency in Python and key libraries such as NumPy, Pandas, scikit-learn, TensorFlow or PyTorch. Basic understanding of machine learning algorithms and model evaluation techniques. Strong analytical and communication skills. Comfortable working in a collaborative environment and taking feedback. Desirable More ❯

and customers 3+ years of experience involving data analytics, machine learning models and AI principles and application in implementation and practical delivery. Experienced in Python development and tooling including Pandas, Scikit-learn or equivalent. A third level qualification in Computer Science, Software Engineering, Data Science or other related discipline. Experience with data exploration and visualisation. A theoretical and practical foundation More ❯

tight deadlines whilst remaining organised Strong analytical approach to problems Technical skills: Proficiency in Python Proficiency with version control (Git) Familiarity with containerisation (Docker) Familiarity with data processing tools (Pandas, NumPy) Experience using machine learning frameworks like PyTorch or TensorFlow Familiarity with cloud platforms and their ML services Benefits: MOST IMPORTANT: Your career Mentorship from senior machine learning engineers Access More ❯

science in finance, insurance or Ecommerce is an advantage but not required Experience of deployment in a cloud environment Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas Experience with API development SQL experience Software engineering experience DevOps/MLOps experience Good working understanding of CI/CD If you hold the experience and technical skills outlined above More ❯

language consistently in data-centric projects. Experience in developing and maintaining pipelines and infrastructure for products or applications, at scale. Strong knowledge of the Python Data Science stack (e.g., pandas/polars, scikit-learn). Ability to independently develop and maintain robust Python-based ETL/ELT data pipelines. Ability to independently develop LLM-based tools/products (e.g., RAG More ❯

ingest data. Consult with internal and external stakeholders then deliver the solution. Experience required: STEM/Computer Science Degree OR sufficient commercial experience Good skills with Python. Use of Pandas is a bonus Experience building Data Pipelines/ETL using Python Experience consuming with REST API services 1 years + commercial experience with Python or languages such as JAVA, PHP More ❯

Well-versed in Python. Strong team player. Strong communication skills. Software Developer tech stack: Python > 3.5 with type hints, data classes, and Flask REST API. Postgres for relational data, Pandas for data analysis, and Google Cloud Pub/Sub for messaging. Cloud Build for automated builds, and Cloud Run/Docker for containerisation. Google Cloud Platform is used for infrastructure. More ❯

Ideally experience with de novo transcriptome assembly, Machine Learning and/or Artificial Intelligence, or experience mining genomic data Experience with Python and libraries such as SciPy, Pytorch, NumPy, Pandas etc. What Next? If you'd like to hear more about this exciting Bioinformatician position, just give me a call or drop me an email, I'd love to chat More ❯

Ideally experience with de novo transcriptome assembly, Machine Learning and/or Artificial Intelligence, or experience mining genomic data Experience with Python and libraries such as SciPy, Pytorch, NumPy, Pandas etc. What Next? If you’d like to hear more about this exciting Bioinformatician position, just give me a call or drop me an email, I’d love to chat More ❯

systems (e.g. Red Hat, Ubuntu) Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus on: Design(Architecting, High-Level Design and Low-Level Design) Development Testing Deployment & Maintenance Experience of More ❯