51 to 75 of 247 Pandas Jobs in the UK

delivering production-ready models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working ...

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 ...

least one primary backend language: Java (Modern Java, Spring Boot, concurrency, low-latency tuning, GC optimization), OR Python (Modern Python, asynchronous programming, NumPy/Pandas, FastAPI), OR .NET/C# (Modern .NET Core, multi-threading, asynchronous I/O, memory profiling). Distributed Systems & Messaging: Strong experience with enterprise messaging ...

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 ...

good understanding of the underlying physical principles related to battery technology, electric vehicles, EV charging, and the energy sector. Python experience (numpy, streamlit, scipy, pandas, matplotlib, plotly, poetry, GIT, scikit-learn and other scientific libraries) Excellent mathematical, analytical and problem-solving ability Excellent professional communication, reporting and presentation skills Excel ...

through university projects, internships or personal projects. Experience with AWS or Google Cloud Platform. Knowledge of Docker and CI/CD concepts. Exposure to Pandas, NumPy, R or machine learning. Interest in scientific, healthcare, biotech or data-focused environments. Whether you're a recent graduate, have completed a placement year ...

including 2+ years building production LLM applications or AI agents. Strong Python experience, including production-grade development with tools such as FastAPI, Pydantic, asyncio, pandas and pytest. Solid experience with R and deployment of Shiny applications. Hands-on knowledge of LLM APIs, agent frameworks, vector search, RAG, connector patterns ...

software development experience, ideally supporting Portfolio Managers, traders, or investment teams. Strong Python development skills, including experience with scientific and data libraries such as pandas, NumPy, SciPy, and related tooling. Experience designing and maintaining production-grade software, including reusable libraries, APIs, data-processing workflows, and automated testing. Experience building data ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

least 2 years’ experience working as a data engineer (ideally consulting/financial services) – salary and level will reflect experience. Proficiency in Python (pandas, numpy) Professional experience with Azure cloud services (AWS/GCP acceptable with deeper experience) Strong experience deploying clean, maintainable, production-level code. Basic understanding ...

life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps. Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Comfortable working with Docker and containerised applications Experience using AWS or similar cloud computing platform Experience delivering machine learning solutions within regulated ...

insurance industry. Exposure to reinsurance, in particular casualty lines, would be a distinct advantage. Excellent Python skills, with demonstrable, production-quality experience using pandas and related libraries for data cleansing, transformation and automation. Experience with Git and collaborative development workflows. Strong SQL, with practical experience of designing relational database schemas ...

products. (We typically use Heroku, but experience with AWS, GCP or others is very welcome.) Experience using Python libraries for data analysis, such as pandas, scikit, numpy, nltk, matplotlib, jupyter. Ability to communicate effectively on both technical and non-technical levels, and to cultivate a supportive environment for more junior ...

professional experience building quantitative trading tools, models, or analytics in a financial or commodities setting Strong Python skills in a scientific computing environment (numpy, pandas, scipy, statsmodels or similar) Solid grounding in statistics, time series analysis, and data modeling; machine learning experience is a plus Experience building data pipelines ...

life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps.- Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc.- Comfortable working with Docker and containerised applications- Experience using AWS or similar cloud computing platform- Experience delivering machine learning solutions within regulated ...

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 ...

Extensive experience with traditional ML algorithms, Deep Learning frameworks, and complex time-series forecasting. Experience developing production-grade Python code: High proficiency in Python, Pandas, and modern software practices (testing, clean code, code review, CI/CD). Data & Pipeline Expertise: Hands-on experience optimizing data models and access patterns ...

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 ...

Extensive experience with traditional ML algorithms, Deep Learning frameworks, and complex time‐series forecasting. Experience developing production‐grade Python code: High proficiency in Python, Pandas, and modern software practices (testing, clean code, code review, CI/CD). Data & Pipeline Expertise: Hands‐on experience optimizing data models and access patterns ...

decisions. Knowledge of foundational model systems and frameworks/best practices for building agents. Experience using Python and common data science libraries such as pandas, scikit-learn, NumPy and visualisation frameworks. Strong SQL skills with experience querying and transforming large datasets, ideally using platforms such as BigQuery, Snowflake, or similar ...

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 ...

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 ...

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 ...

starting ASAP, with a hybrid working model (3 days per week in the London office). Specific skills/experience required: Strong Python (3.11+), pandas and NumPy skills. Production-grade Streamlit dashboard development. Data integration using Snowflake, OpenSearch, REST APIs and SQL. AWS experience (boto3, S3, Parquet). Data visualisation ...