1 to 25 of 86 DemandTrendPermanent Pandas Jobs in the UK

Fixed Income Credit Rates Bonds ABS Vue Angular React Agile AWS GCP Buy Side Asset Manager Investment Management Performance Risk Attribution TypeScript Node Finance Front Office Trading Financial Services Pandas Numpy Scipy) required by our asset management client in London. You will join a team of 4 that is responsible for an in-house built order tracking and communication platform. More ❯

of Trading terminology and concepts (incl. financial derivatives), gained from experience working in a Trading or Finance environment Expert in core Python with Python scientific stack/ecosystem (including pandas, numpy, scipy, stats), and a second strongly typed language (e.g.: C#, C++, Rust or Java) Expert in application design, security, release, testing and packaging Mastery of SQL/no-SQL More ❯

frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Strong skills in data preprocessing, wrangling, and augmentation techniques Experience More ❯

graduate full stack developer to work on portal development, back-end business logic and data analytics.Experience as a Python Developer, working on data intensive numerical applications (E.g. Using Numpy, Pandas)Experience with the all stages of the software development lifecycle from product design, technical design, coding, testing, documentation, release into production and ongoing maintenance Experience working with AWS python SDK More ❯

platforms 5+ years working with front office stakeholders, including traders and researchers to fulfil their data needs Experience performing data analysis in SQL and Python using common libraries like pandas Experience using cloud-based tools like AWS S3 or Snowflake Strong organizational and relationship management skills The annual base salary range for this position is $100,000 to More ❯

rapid MVP development and iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification More ❯

in finance, data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders More ❯

in finance, data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders More ❯

in finance, data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders More ❯

in finance, data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders More ❯

in finance, data science, or a closely related field Strong understanding of macroeconomics, financial markets, and investment principles Proficiency in Python, with experience in data manipulation libraries such as pandas and NumPy Strong analytical skills with the ability to design efficient data pipelines and workflows Excellent communication skills, able to convey complex concepts to both technical and non-technical stakeholders More ❯

engineering, ideally in front office finance , fintech , high-frequency trading , or technology-driven startups Expert-level Python skills - designing, debugging, and optimizing complex applications Very strong data capabilities with Pandas , NumPy , SQL , real-time data processing, and ETL Familiarity with DevOps practices including Linux , cloud platforms , CI/CD , and containerization (Docker/Kubernetes desirable) Proven ability as a live More ❯

Science, Engineering, Mathematics, Statistics, or a related field. 6+ years of experience in ML Engineering or Data Science (finance, fintech, or treasury a plus). Proficiency in Python-including pandas, scikit learn, TensorFlow/PyTorch, LightGBM/XGBoost-and experience with SQL. Hands on experience with cloud ML platforms (AWS SageMaker, Azure ML, or Google AI Platform). Solid understanding More ❯

engineers and contribute to best practices across the team. Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure More ❯

engineers and contribute to best practices across the team. Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure 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 ❯

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 ❯

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 ❯

/ML algorithms and techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training More ❯

Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects 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 ❯

Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid More ❯

Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid More ❯