1 to 25 of 46 Pandas Jobs in the South East

Essential skills/experience: Proven track record of delivering commercial value using supervised machine learning techniques. Advanced Python programmer, and experience with data manipulation and analysis libraries (e.g., NumPy, Pandas, scikit-learn) Advanced knowledge of data science technologies including tooling and platforms. Proficient in SQL and Git. Ability to drive projects from initiation to completion. Keen interest in emerging Machine 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

manage technical priorities, meet deadlines, and deliver on project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong foundations in applied mathematics 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 ❯

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 ❯

science, ideally within a commercial or trading environment Proficiency in time series analysis, regression modelling, and forecasting techniques Strong experience with Python and core libraries for data science (e.g., pandas, NumPy, scikit-learn, statsmodels) Ability to manipulate and analyse large, complex datasets with attention to detail Clear, confident communicator who can explain analytics and influence commercial decisions Experience using visualisation 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 ❯

pipelines and evaluation frameworks. Collaborate with data scientists, software engineers, and domain experts to deliver high-impact solutions. Essential Skills Expert-level Python programming with libraries such as NumPy, Pandas, Scikit-learn, LangChain, LlamaIndex, and Azure AI Foundry. Strong experience with Azure and generative AI R&D. Practical knowledge of GenAI techniques including prompt orchestration, retrieval methods, and agentic frameworks 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 ❯

in Data Analysis, with approx. 4+ years in a senior or equivalent role. Strong experience in SQL (writing and optimising complex queries). Proficiency in Python (including libraries like Pandas, NumPy, SQLAlchemy). Experience working with large datasets , and advanced data modelling techniques. Ability to engage with stakeholders and translate their needs into actionable data solutions. Solid understanding of data More ❯

in Data Analysis, with approx. 4+ years in a senior or equivalent role. Strong experience in SQL (writing and optimising complex queries). Proficiency in Python (including libraries like Pandas, NumPy, SQLAlchemy). Experience working with large datasets , and advanced data modelling techniques. Ability to engage with stakeholders and translate their needs into actionable data solutions. Solid understanding of data More ❯

Looking For: Strong programming skills in Python (PyTorch, Hugging Face, scikit-learn). Experience with fine-tuning/adapting pre-trained AI models . Solid data handling skills (SQL, Pandas, preprocessing for text, audio, or images). Familiarity with model deployment (FastAPI, Flask, Docker, cloud services). Experience working with APIs and integrating AI into practical tools. Bonus if you More ❯

curious and eager to learn. We'll help you build these skills. Experience with: Automation of processes/pipelines for data, analytics or operations ML-specific Python libraries (e.g. pandas, scikit-learn, xgboost) Big data tooling (e.g. Snowflake/snowpark, pyspark) Cloud computing - especially Azure, where we deploy key parts of our platform The interview process: Our interview process involves 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 ❯