51 to 75 of 89 Pandas Jobs in London

quality, documentation, and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

accuracy. Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads More ❯

accuracy. Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads More ❯

analytics, or similar roles, with at least 2 years in fintech, payments, or financial services. Solid grounding in statistics, machine learning, and data engineering principles. Experience with Python (e.g., pandas, scikit-learn, seaborn) and SQL (Postgres preferred) for advanced data manipulation. Familiarity with the modern data stack (Databricks). Strong track record of delivering commercial and operational impact through data More ❯

gradient-boosted models (e.g., XGBoost, LightGBM) and/or building LLM-powered systems (e.g. tool/function calling, prompt design, evals) for text-heavy tasks. Solid data skills: SQL, pandas, experiment tracking, and cloud deployment (AWS a plus). A passion for AI/ML, shown through personal projects, a well-maintained GitHub portfolio, blog posts, or contributions to the More ❯

on Data Science operations Technical Skills: Python Proficiency: Strong Python programming skills, with experience in developing and maintaining analytics packages and tools. Familiarity with data science libraries such as pandas and scikit-learn SQL: Proficient in SQL, particularly with cloud data warehouses like Snowflake Statistical Methodology: In-depth knowledge of GLMs and other machine learning algorithms Data Tools: Familiarity with More ❯

Azure Occasionally the employee might be part of collaborations across different teams and must report to different project managers.Role Requirements Advanced programming with Python and related data science libraries (pandas, numpy, scipy, etc) at least 2 years, possibly at production level Data science skills: statistical analyses, machine learning techniques. Previous experience in statistical matching and segmentation techniques is a great More ❯

/Unix computing environment and High Performance Computing (HPC). Knowledge of statistics and experience with statistical software and data processing modules such as R and python modules including pandas, numpy and Matplotlib. Experience in data presentation and statistical analyses. Desirable Experience in a diagnostic laboratory. Experience participating in collaborative research projects. Some experience of research in a clinical environment. More ❯

and communicate findings in a clear, concise manner. Collaborate with the data engineering team to maintain good data hygiene and integration. Essential Requirements Proficiency in Python for data analysis (pandas, NumPy, matplotlib/seaborn). Solid foundation in statistics: distributions, hypothesis testing, confidence intervals, regression. Experience working with structured datasets Ability to produce clear, well-commented code and visual outputs More ❯

to drive results. What you'll bring Minimum bachelors degree in a STEM subject at a reputable academic institution. 3+ years professional experience in Python including use of NumPy, Pandas and other scientific libraries. Experience working in a Linux environment. A desire to work closely with Researchers and accelerate their research. The ability to self-manage, self-motivate, and seek More ❯

to drive results. What you'll bring Minimum bachelors degree in a STEM subject at a reputable academic institution. 3+ years professional experience in Python including use of NumPy, Pandas and other scientific libraries. Experience working in a Linux environment. A desire to work closely with Researchers and accelerate their research. The ability to self-manage, self-motivate, and seek More ❯

to drive results. What you'll bring Minimum bachelors degree in a STEM subject at a reputable academic institution. 3+ years professional experience in Python including use of NumPy, Pandas and other scientific libraries. Experience working in a Linux environment. A desire to work closely with Researchers and accelerate their research. The ability to self-manage, self-motivate, and seek More ❯

to drive results. What you'll bring Minimum bachelors degree in a STEM subject at a reputable academic institution. 3+ years professional experience in Python including use of NumPy, Pandas and other scientific libraries. Experience working in a Linux environment. A desire to work closely with Researchers and accelerate their research. The ability to self-manage, self-motivate, and seek More ❯

Bring 3+ years experience in Generative AI experience Proven experience with language-based Generative AI eg. LangChain, LangSmith, LangGraph, RAG, Proficiency in Python, data science libraries such as numpy, Pandas, scikit-learn Experienced in LLM frameworks such as LangChain Ability to build and create prototypes in a fast-paced environment BSc/MSc in Computer Science, Physics, Mathematics, Engineering, or More ❯

in sport, gaming, or similar domains with forecasting needs. 2+ years working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational More ❯

Bring 3+ years experience in Generative AI experience Proven experience with language-based Generative AI eg. LangChain, LangSmith, LangGraph, RAG, Proficiency in Python, data science libraries such as numpy, Pandas, scikit-learn Experienced in LLM frameworks such as LangChain Strong client-facing consulting or B2B experience Ability to build and create prototypes in a fast-paced environment BSc/MSc More ❯

using different analysis techniques to 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 and analytical skills High attention More ❯

Data Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g. More ❯

industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big data and scalable model More ❯

state-of-the-art areas (e.g. NLP, Transfer Learning) and modern Deep Learning algorithms (e.g. BERT, LSTM) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit-Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data) Solid understanding of statistics; hypothesis testing, probability distributions, sampling techniques Private Health Care More ❯

experience in a data science or analytics role, preferably within the AI/ML industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision More ❯

experience in a data science or analytics role, preferably within the AI/ML industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision More ❯

experience in a data science or analytics role, preferably within the AI/ML industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision More ❯

experience in a data science or analytics role, preferably within the AI/ML industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision More ❯

analytics and hands-on experience and solid understanding of machine learning and deep learning methodsExtensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goalsExperience with big data and scalable model training More ❯