26 to 50 of 55 Pandas Jobs in London

or Chatbors, particular voice, is a must-have. Strong recent hands-on capabilities in Python are a must-have. Experience with a microservice environment using tools such as Jupyter, Pandas, Numpy, Fast API, and SQL alchemy is a must. Srong's understanding of deploying and supporting LLM’s in a production environment is a must-have. An interest and understanding More ❯

the latest developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

the latest developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

applications and familiar with the concepts of MCP servers, Agents, and Retrieval-Augmented Generation (RAG) systems. Experience with extract, transform, and load (ETL) data with using Python libraries (e.g. Pandas). Strong understanding of version control systems and CI/CD pipelines to streamline development workflows and proficient with tools such as Git, and Jenkins. Automated data analytics and reporting More ❯

requirements for data pipelines and feature engineering Promote best practices in data science, model validation, documentation, and reproducibility Qualifications Experience Strong coding skills in Python, including libraries such as pandas, scikit-learn, TensorFlow, or PyTorch Expert in Python and ML frameworks (PyTorch, TensorFlow, Sklearn), with experience across NLP, computer vision, and LLMs Strong statistical and experimental design background, including A 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 ❯

not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯

not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯

Vision, or related technical discipline. Good knowledge of machine learning and computer vision algorithms. Familiarity with real-time imaging pipelines. Experience with scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit's, etc. Experience in standard software engineering practices including version control systems and software testing methodologies. Excellent oral and written communication skills. Analytical thinker, attentive to details 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 ❯

. Utilise SQL for data extraction, transformation, and analysis. Skills & Experience Proven experience working as a Pricing Analyst. Strong proficiency in SQL and Python (including data libraries such as pandas, NumPy, scikit-learn, etc.) Skilled in Power BI or equivalent visualisation platforms. Background in retail, ticketing, or loyalty environments preferred. Experience in clustering, segmentation, and data modelling. Location: Shepherds Bush More ❯

. Utilise SQL for data extraction, transformation, and analysis. Skills & Experience Proven experience working as a Pricing Analyst. Strong proficiency in SQL and Python (including data libraries such as pandas, NumPy, scikit-learn, etc.) Skilled in Power BI or equivalent visualisation platforms. Background in retail, ticketing, or loyalty environments preferred. Experience in clustering, segmentation, and data modelling. Location: Shepherd's More ❯

research and insights. What we're looking for: Strong hands-on experience with time-series modelling (ARIMA, VAR, GARCH, Prophet, LSTMs, Transformers, etc.). Proficiency in the Python ecosystem (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow; polars/dask a plus). Familiarity with SQL and handling large datasets. Curiosity and interest in financial markets and macroeconomics . Master's 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 ❯

across EMEA to drive productivity and efficiency. Own sales operations functions including pipeline management, incentive compensation, deal desk, lead management, and contact centre operations . Use SQL and Python (Pandas, PySpark) to analyse data, automate workflows, and generate insights. Design and manage ETL/ELT processes, data models, and reporting automation . Leverage Databricks, Snowflake, and GCP to enable scalable 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 ❯

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 ❯

multimodal foundation models and generative AI frameworks' exploration, development, and implementation. Extensive experience with common machine learning Python frameworks such as TensorFlow and PyTorch; and Python libraries such as pandas, and computer vision libraries such as OpenCV. Experience in ONNX and TensorRT. Very comfortable working in Linux environment. Familiarity with software development tools and agile development practices. 6 years experience More ❯

degree in a quantitative field (e.g. Statistics, Mathematics, Physics, Machine Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural 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 ❯

a focus on areas such as robustness, explainability, or uncertainty estimation. Advanced programming and mathematical skills with Python and an experience with the standard Python data science stack (NumPy, pandas, Scikit-learn etc.). The ability to conduct and oversee complex technical research projects. A passion for leading and developing technical teams; adopting a caring attitude towards the personal and More ❯

with exposure to Natural Gas and Power markets, balancing mechanisms, and regulatory frameworks (e.g., REMIT, EMIR). Expert in Python and SQL; strong experience with data engineering libraries (e.g., Pandas, PySpark, Dask). Deep knowledge of ETL/ELT frameworks and orchestration tools (e.g., Airflow, Azure Data Factory, Dagster). Proficient in cloud platforms (preferably Azure) and services such as 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 ❯