201 to 221 of 221 Pandas Jobs in England

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

pressure). Communicate findings effectively to both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics. Knowledge of advanced football metrics (possession value models highly desirable). A deep passion More ❯

pressure). Communicate findings effectively to both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics. Knowledge of advanced football metrics (possession value models highly desirable). A deep passion More ❯

pressure). Communicate findings effectively to both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics or personal projects related to football data. Knowledge of advanced football metrics (possession value More ❯

pressure). Communicate findings effectively to both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics. Knowledge of advanced football metrics (possession value models highly desirable). A deep passion More ❯

pressure). Communicate findings effectively to both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics. Knowledge of advanced football metrics (possession value models highly desirable). A deep passion More ❯

pressure). Communicate findings effectively to both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics. Knowledge of advanced football metrics (possession value models highly desirable). A deep passion More ❯

and reporting tools. Core Responsibilities Develop, fine-tune, and deploy transformer-based NLP models (LLMs, BERT, RoBERTa, GPT-family). Design and implement scalable data pipelines using Python, spaCy, Pandas, and Hugging Face Transformers. Build or enhance retrieval-augmented generation (RAG) systems using LangChain and vector databases like FAISS, Weaviate, or Pinecone. Package and deploy solutions via Docker, Kubernetes, or More ❯

Python Programming ii. Key skills: Functions, classes, and object-oriented programming, List comprehensions, generators, Error handling, iii. Working with virtual environments and package management (pip, venv) Data Manipulation & Analysis (Pandas & NumPy) i. Key libraries: pandas, numpy, (optional: polars) ii. Key skills: Data cleaning and preprocessing, Handling missing values, grouping, merging, pivoting, aggregations, and SQL Software Engineering Best Practices i. Key More ❯

Strong fundamentals in software engineering: testing, version control, CI/CD, clean architecture Passion for building internal tools, research frameworks, or working on data-heavy systems Bonus: Exposure to pandas, NumPy, asyncio, Cython, or PyArrow. Familiarity with C++ is a plus Bonus++: Experience working with quants, data scientists, or in trading environments Tech Stack: Python 3.11+ (fast, modern, typed) Dask … pandas, PyArrow, NumPy PostgreSQL, Parquet, S3 Airflow, Docker, Kubernetes, GitLab CI Internal frameworks built for scale and speed Why Join: Engineers own projects end-to-end—from design to deployment to impact Work side-by-side with quants, traders, and researchers in a flat, fast-moving team Competitive compensation at the top of the market, with research-aligned bonuses No More ❯

tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯

tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯

secure, scalable, and maintainable applications using Python and Azure cloud technologies for commodities trading solutions. Leverage strong proficiency in Python, including use of numerical and scientific libraries such as Pandas, NumPy, SciPy etc. Utilize a second strongly typed programming language (e.g., C#, C++, Rust, or Java) as needed. Implement application architecture and DevOps best practices, including Infrastructure as code, Kubernetes … requirements into technical specifications and software products. Mandatory Skills Extensive experience in Python application development, especially within trading, finance, or quantitative domains. Proficiency with major Python numerical libraries (e.g., pandas, numpy, scipy, stats). Experience with at least one additional strongly typed programming language (C#, C++, Rust, Java, etc.). Strong background in Azure cloud application development, including security, observability More ❯

to hear from you if you Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience productionising machine learning models Are an expert in one of predictive modeling, classification, regression, optimisation or recommendation systems Have experience with Spark Have knowledge … tuning, RAG, agents) Experience with graph technology and/or algorithms, understanding of NLP algorithms Our technology stack Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOp/DevOps: Terraform, Docker, Airflow, MLFlow, NewRelic The interview process Recruiter Call (30 minutes) Meeting a Machine Learning Manager More ❯

Inside IR35 Contract Proficient Python Programming Functions, classes, and object-oriented programming, List comprehensions, generators, Error handling, Working with virtual environments and package management (pip, venv) Data Manipulation & Analysis (Pandas & NumPy) Key libraries: pandas, numpy, (optional: polars) Key skills: Data cleaning and preprocessing, Handling missing values, grouping, merging, pivoting, aggregations, and SQL Software Engineering Best Practices Key practices: Version control More ❯

Inside IR35 Contract Proficient Python Programming Functions, classes, and object-oriented programming, List comprehensions, generators, Error handling, Working with virtual environments and package management (pip, venv) Data Manipulation & Analysis (Pandas & NumPy) Key libraries: pandas, numpy, (optional: polars) Key skills: Data cleaning and preprocessing, Handling missing values, grouping, merging, pivoting, aggregations, and SQL Software Engineering Best Practices Key practices: Version control More ❯

with: Proficient Python Programming Key skills: Functions, classes, and object-oriented programming, List comprehensions, generators, Error handling, Working with virtual environments and package management (pip, venv) Data Manipulation & Analysis (Pandas & NumPy) Key libraries: pandas, numpy, (optional: polars) Key skills: Data cleaning and preprocessing, Handling missing values, grouping, merging, pivoting, aggregations, and SQL Software Engineering Best Practices Key practices: Version control More ❯

We are looking for someone who gets their hands dirty with the data, produces actionable insights, and automates everything they can. WHAT YOU’LL DO Use SQL and Python (pandas, NumPy) daily to clean, join and transform data into analysis-ready tables. Build and maintain lightweight automated pipelines to refresh reports and validate data with minimal manual intervention. Create and … control (Git) for reproducibility. WHAT WE’RE LOOKING FOR Technical Skills – Must Have Strong SQL : confident writing complex queries, joining large datasets, and optimising performance. Strong Python : comfortable with pandas, NumPy, and writing automation scripts. Looker (or similar BI tool) : able to create and maintain dashboards; happy to cross-train if experienced in Tableau or Power BI. Understanding of data More ❯

and development of junior team members. Support senior team members in identifying and addressing data science opportunities. Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML … principles and version control (e.g., Git). Excellent problem-solving skills and ability to work independently or in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML More ❯

About the roleWe are excited to be hiring a new Data Scientist into our team! Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits More ❯

in common: a curiosity for learning, a drive to deliver projects brilliantly, and a belief that together we make a difference. Using your expertise in Azure Machine Learning, Python (pandas, scikit-learn) and Azure SDKs, you will help shape our Data & Productivity capability—designing, training, and deploying models with MLflow/AutoML, and integrating them into real business processes. You … design, delivery, and governance across the ML and AI lifecycle. Experienced in designing, training, registering, and deploying models using Azure Machine Learning (AML), AutoML, and MLflow. Proficient in Python, pandas, and scikit-learn for data science and feature engineering, with a strong focus on rigorous validation and experiment tracking. Skilled in deploying models to real-time REST endpoints and orchestrating More ❯