1 to 25 of 44 Pandas Jobs in the South East

data validation processes Ensure integration with internal data sources and reporting tools Required Skills 5+ years of Python development experience, ideally in financial services or commodities Strong proficiency in Pandas , NumPy , and time-series data manipulation Proven experience with FastAPI or Flask Familiarity with large datasets and real-time data pipelines Excellent debugging, profiling, and performance optimization skills Strong communication More ❯

are a plus) Solid understanding of software architecture, algorithms, data structures and computer science fundamentals Interest or experience in quant finance Advanced knowledge of the python data science stack (Pandas, NumPy, SciPy) is a plus Strong academic background from a top tier university a major plus If this sounds of interest we'd love to hear from you! Vertex Search More ❯

are a plus) Solid understanding of software architecture, algorithms, data structures and computer science fundamentals Interest or experience in quant finance Advanced knowledge of the python data science stack (Pandas, NumPy, SciPy) is a plus Strong academic background from a top tier university a major plus If this sounds of interest we'd love to hear from you! Vertex Search More ❯

are a plus) Solid understanding of software architecture, algorithms, data structures and computer science fundamentals Interest or experience in quant finance Advanced knowledge of the python data science stack (Pandas, NumPy, SciPy) is a plus Strong academic background from a top tier university a major plus If this sounds of interest we'd love to hear from you! Vertex Search More ❯

data validation processes. Integrate with market data, storage systems, and reporting platforms. Required Skills 5+ years' Python development experience, ideally within trading, risk, or financial services. Strong background with Pandas, NumPy, and data science libraries . Hands-on experience with Flask or FastAPI for API development. Proficiency in time-series data manipulation and back-testing methods. Experience working with large More ❯

driven solutions within the asset management, investments, or reinsurance domain. Work with cross-functional teams to capture requirements and deliver effective outcomes. Must-Have Skills & Experience Strong Python skills (Pandas, NumPy). Advanced SQL for data querying and manipulation. Hands-on experience with Google Cloud Platform (GCP) and BigQuery. Background in asset management, investments, or reinsurance operations (within the last More ❯

Services - Mandatory Good understanding of quantitative finance Good experience developing and optimising Python-based calculators and models. Strong experience developing high-performance APIs using Flask or FastAPI. Expertise in Pandas, NumPy and other computing libraries. Strong experience liaising with front-office stakeholders What you'll get in return Initial 6-month contract with extensions Up to £700pd umbrella London-based More ❯

Services - Mandatory Good understanding of quantitative finance Good experience developing and optimising Python-based calculators and models. Strong experience developing high-performance APIs using Flask or FastAPI. Expertise in Pandas, NumPy and other computing libraries. Strong experience liaising with front-office stakeholders What you'll get in return Initial 6-month contract with extensions Up to £700pd umbrella London-based 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 ❯

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 ❯

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 ❯

s or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation More ❯

s or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation More ❯

AI requirements into scalable solutions. Essential Experience & Skills 5+ years' engineering experience, with at least 3 years in ML Ops, Data Engineering, or AI infrastructure. Strong Python engineering skills (Pandas, Numpy, Jupyter, FastAPI, SQLAlchemy). Expertise in AWS services (certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

skills. Bonus skills • Experience deploying and managing applications with Azure and Docker. • Familiarity with frameworks like LangChain and Retrieval-Augmented Generation (RAG) models for AI-driven applications. • Experience with pandas for data manipulation. What’s on offer • Regular salary reviews recognising performance and contribution. • Generous annual leave: 25 days plus three days over Christmas. • Flexible hybrid working to support work More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from 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 ❯

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 ❯

and refining them to strong results. Experienced in engaging with non-technical partners to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with More ❯