26 to 50 of 75 Pandas Jobs in the UK

Experience Required Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science ...

designing and managing workflows for collecting, cleaning, and storing large volumes of financial data (e.g., price, volume, fundamentals, alternative data), often using tools like Pandas, NumPy, and Dask. Collaborate Across Teams for Deployment, working with researchers, traders, and DevOps teams to integrate Python models into production environments (e.g., through APIs ...

foster collaboration and drive improvements. Qualifications Must-Have Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets. AI/ ...

foster collaboration and drive improvements. Qualifications Must-Have Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets. AI/ ...

foster collaboration and drive improvements. Qualifications Must-Have Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets. AI/ ...

foster collaboration and drive improvements. Qualifications Must-Have Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets. AI/ ...

/ML, LLMs (GPT, Claude) and Generative AI . Proven experience with Agentic AI tools, GitHub Copilot, MCPs . Advanced Python skills – NLTK, NumPy, Pandas, Scikit-learn. Good understanding of AI/ML algorithms (Regression, Classification, Decision Trees, KNN, K-Means). Experience developing AI-enhanced test automation solutions. Solid ...

Were looking for a talented ML Ops Engineer to join our growing teams. Key Responsibilities 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 ...

Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. ...

Advanced Analytics! Responsibilities Leverage data preparation, analysis, and predictive modelling techniques to address business challenges. Develop and implement scripts for data manipulation using Python, Pandas, NumPy, and Dask. Create visualizations using Matplotlib, Seaborn, and Plotly to communicate insights effectively. Collaborate with cross-functional teams to integrate data-driven solutions into ...

/supporting/principles. Current Microsoft/Databricks certifications are useful but not mandatory – we’ll help you get those! Core: Data Manipulation (SQL, Pandas, Pyspark) Azure AI (Azure AI Foundry, AI Search, Document Intelligence, AI Services) Data Science & Machine Learning (Databricks, Python, SKLearn, XGBoost, MLFlow, EDA) Familiarity with LLMs ...

learning, delivering actionable insights and business optimisation solutions. Technical Excellence: Deep proficiency in Python, possibly R for prototyping, SQL, and specialist tools such as Pandas, NumPy, Spark, and Dask; hands-on experience with cloud platforms (Azure ML, AWS) and ML Ops for robust model deployment and automation. CI/ ...

system behavior. AI/ML for QA (Preferred): Experience applying data science or machine learning techniques to solve testing problems. Familiarity with libraries like Pandas, NumPy, SciPy, and scikit-learn is a strong plus. Scripting: Proficiency in Bash is a must. Bonus points for Go or C++ experience. Leadership & Soft ...

Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some ...

Ideal Qualifications Have strong professional experience in data science or applied analytics. Skilled in Python and Jupyter notebooks. Have experience using libraries including numpy, pandas, scipy, sympy, scikit-learn, torch, tensorflow. Have a strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine ...

medals or top-tier rankings). Strong experience in data science, analytics, or ML-driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. ...

Familiarity with SAP data structures is beneficial Integration with PIM (Product Information Management) systems Design and consumption of REST APIs Programming & Querying Python (advanced): pandas, numpy, boto3, and data processing best practices SQL (advanced): complex queries, performance tuning, and query optimization Data Quality & Governance Data profiling and ongoing quality assessment ...

Familiarity with SAP data structures is beneficial Integration with PIM (Product Information Management) systems Design and consumption of REST APIs Programming & Querying Python (advanced): pandas, numpy, boto3, and data processing best practices SQL (advanced): complex queries, performance tuning, and query optimization Data Quality & Governance Data profiling and ongoing quality assessment ...

volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another ...

volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another ...

models that perform reliably in complex operational environments. What We’re Looking For Strong experience in Python and SQL, including libraries such as Pandas, NumPy and scikit-learn. Experience working with deep learning frameworks such as PyTorch or TensorFlow. A solid grounding in statistics and probability, with strong mathematical foundations ...

Deep expertise in ML, statistical modelling, and modern AI techniques (supervised/unsupervised, time-series, Bayesian, deep learning). 🐍 Strong Python engineering skills — NumPy, Pandas, Scikit-Learn, plus PyTorch/TensorFlow. 🏗 Experience building scalable ML systems in production (ML Ops, CI/CD for ML, model optimisation). 🚀 Proven experience ...

draw insight from data, using tools such as Python and SQL Excellent Python, including relevant libraries for data analysis and machine learning (e.g. sklearn, Pandas, NumPy) and at least one deep learning framework Excellent communication skills through written reports and presentations Organisational skills (e.g. planning, time management) Strong problem-solving ...

supervised/unsupervised learning, Bayesian inference, time-series analysis). You possess strong Python skills and excellent proficiency with core data science libraries (NumPy, Pandas, Scikit-Learn), plus familiarity with deep-learning frameworks (TensorFlow, PyTorch). You have proven experience leading data science projects, making key decisions on technical direction ...

clustering, time-series forecasting, survival analysis). Solid object-oriented programming skills in Python and hands-on expertise with the core data science stack (Pandas, Numpy, Scikit-learn, XGBoost/LightGBM). A proven ability to break down vague, complex problems into concrete, solvable steps. Excellent communication and data storytelling ...