1 to 25 of 268 Pandas Jobs in the UK

Statistics, Physics, or related); Master's degree preferred. Professional software development experience, with deep expertise in Python and its data/engineering ecosystem (e.g., pandas, NumPy, FastAPI, orchestration tools). Proven track record of delivering production-grade automation, data pipelines, or testing frameworks in a complex enterprise environment; financial services ...

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 ...

data warehouses, lakehouse environments or analytics tools such as Power BI. Familiarity with modern data engineering frameworks and tools (e.g. Spark/PySpark, Pandas, orchestration tools). Experience with cloud data platforms on AWS or Azure (e.g. Databricks, Redshift, Microsoft Fabric). Understanding of software engineering fundamentals, including Git, testing ...

experience with AWS cloud services for machine learning and data engineering Proficiency in Python and data science libraries including scikit-learn, TensorFlow, Keras, Pandas and Seaborn Solid understanding of SQL and experience with NoSQL databases Hands-on experience building NLP, LLM, RAG and agentic AI solutions using frameworks such ...

Docker and Kubernetes for scalable production systemsFamiliarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)Exposure to DevOps, DataOps, and MLOps concepts and best practicesExperience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/ ...

pipelines in a professional setting (e.g., internship) is a plusAbility to write clean, maintainable, scalable, and robust code in PythonFamiliarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)Basic understanding or exposure to containerization technologies such as Docker ...

judge whether results are both statistically and commercially credible. Strong Python or R and SQL skills (joins, CTEs, window functions), with libraries such as pandas, NumPy, scikit-learn, statsmodels, or SciPy — and explainability tools like SHAP. Fluent in commercial concepts (ROI, ROAS, incremental revenue, margin, market share) and comfortable partnering ...

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 ...

models What We’re Looking For: Essential Skills & Experience Proven experience solving complex, real-world problems using data science and analytics Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics Deep understanding of machine learning methods and their practical application Experience delivering multiple ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

engineering fundamentals: working with Parquet, Hive-partitioned datasets, and SQL against large tables (Athena/Presto). Solid working knowledge of the PyData stack — pandas and NumPy for data manipulation, Jupyter for experimentation, matplotlib/Seaborn for visualisation — and experience troubleshooting data-quality issues. Testing discipline with PyTest ...

translate business problems into measurable analytical outcomes.* Experience taking models from development into production environments.### Technical Skills* Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

skills Experience of cloud platforms (AWS, Azure, or GCP) Experience of containerisation (Docker) and orchestration (Kubernetes) Exposure to data engineering tools/libraries (e.g. Pandas, NumPy) or NLP libraries Knowledge of message queues/event-driven architecture (e.g. RabbitMQ, Kafka) Understanding of CI/CD tools (e.g. Jenkins, GitHub Actions ...

Excellent communication skills with the ability to communicate concepts clearly and precisely Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES Experience as a Data Architect or Senior Manager Proven track record ...

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 ...

ability to translate business problems into measurable analytical outcomes. Experience taking models from development into production environments. Technical SkillsPython and associated data science ecosystem (Pandas, NumPy, Scikit-learn).Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

from concept through to production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative ...

data experience, and a passion for building scalable, high-quality ML and data solutions in production environments. Essential Experience Strong programming skills in Python (Pandas, NumPy, etc.). Proficiency in SQL for data querying and transformation. Hands-on experience with Machine Learning techniques and frameworks (e.g., scikit-learn, TensorFlow, PyTorch ...

Python and SQL. Practical experience with Kotlin, Java, or modern JavaScript frameworks is highly desirable. Data Processing & Storage: Practical experience using PySpark, Spark, or Pandas for large complex datasets and relational/graph data models. Cloud & Infrastructure: Hands-on experience with AWS services, Infrastructure as Code (Terraform), Docker, Kubernetes ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

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 ...

analytical outcomes. Desirable Requirements Experience working in a Lloyd's syndicate, managing agent, London Market broker or specialty (re)insurer. Python for data analysis (pandas/notebooks). Hands-on experience applying AI/LLM tooling to analytics work. Experience with Microsoft Fabric, dbt, Azure DevOps/GitHub Actions ...

stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.).Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium ...

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 ...