21 of 21 Remote Pandas Jobs in London

Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable) * Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies * Some knowledge More ❯

reliability and accuracy. Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud More ❯

vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with More ❯

vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with More ❯

meaningful insights from structured and unstructured datasets of varying sizes. Track record of implementing impactful models that drive sustained business results. Proficiency in the Python data science tech stack (pandas, scikit-learn, NumPy, and visualisation libraries) Experience working in a Linux-based cloud environment (e.g. GCP, Azure, AWS). Experience using git version control. Communication, stakeholder management, and problem-solving More ❯

Required Skills & Experience: Bachelor's degree in Computer Science, Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy, sklearn) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills More ❯

or similar domains with forecasting needs. Skills and competencies Essential: Experience 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 ❯

or similar domains with forecasting needs. Skills and competencies Essential: Experience 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 ❯

in a fast-paced, high-growth environment. You are comfortable with ambiguity and changing priorities. Bonus Points: Experience in FinTech or eCommerce domains. Experience with Python for data analysis (Pandas, NumPy). Familiarity with data orchestration tools (e.g., Airflow, Dagster). Experience setting up data quality monitoring and alerting. What to Expect After You Apply You can expect to hear More ❯

ingest data. Consult with internal and external stakeholders then deliver the solution. Experience required: STEM/Computer Science Degree OR sufficient commercial experience Good skills with Python. Use of Pandas is a bonus Experience building Data Pipelines/ETL using Python Experience consuming with REST API services 1 years commercial experience with Python or languages such as JAVA, PHP, Go More ❯

temporal modeling and deep learning. Document methods and support reproducibility, validation, and publication where appropriate. Essential Requirements Strong programming and modeling skills in Python (NumPy, PyTorch or TensorFlow, SciPy, pandas). In-depth knowledge of machine learning for time-series, including RNNs, LSTMs, GRUs, transformers, attention mechanisms. Solid understanding of probabilistic models (HMMs, Bayesian inference, graphical models). Experience designing More ❯

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 ❯

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 ❯

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 ❯

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 ❯

underwriting, fraud, and customer conversion. A hands on role, working with both structured and unstructured data in a fast-paced, collaborative team. What We’re Looking For Strong Python (pandas, sklearn, etc.) and advanced SQL Experience in behavioural or credit models Good understanding of ML algorithms Clear communicator across technical and non-technical teams Knowledge of data drift and model More ❯

underwriting, fraud, and customer conversion. A hands on role, working with both structured and unstructured data in a fast-paced, collaborative team. What We’re Looking For Strong Python (pandas, sklearn, etc.) and advanced SQL Experience in behavioural or credit models Good understanding of ML algorithms Clear communicator across technical and non-technical teams Knowledge of data drift and model 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 ❯

hands-on, end-to-end, and you'll be working with both structured and unstructured data in a fast-moving, collaborative team. What we're looking for Strrong Python (pandas, sklearn, etc.) and advanced SQL Experience building behavioural or credit models Solid understanding of ML algorithms (not just how to run them) Clear communicator across tech and non-tech teams 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 ❯