1 to 25 of 27 Pandas Jobs in the City of London

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 ❯

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 ❯

experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data pipelines Excellent 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 ❯

automatically extract key clauses from contracts, applying NLP to analyse case law, or building a compliance risk prediction tool using large language models. Strong programming skills in Python (NumPy, pandas, scikit-learn, matplotlib); R is also welcome. A solid understanding of core ML concepts, NLP techniques, data wrangling, and model evaluation. Proficiency with SQL and experience handling large, unstructured datasets. More ❯

automatically extract key clauses from contracts, applying NLP to analyse case law, or building a compliance risk prediction tool using large language models. Strong programming skills in Python (NumPy, pandas, scikit-learn, matplotlib); R is also welcome. A solid understanding of core ML concepts, NLP techniques, data wrangling, and model evaluation. Proficiency with SQL and experience handling large, unstructured datasets. 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 ❯

accuracy. Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads More ❯

insights into actionable strategies. Your Skills & Experience We’re looking for a Data Scientist with: Strong experience in predictive modeling, customer analytics, or marketing data science. Proficiency in Python (Pandas, NumPy, Sci-Kit Learn) or similar tools. A proven track record of delivering impactful, data-driven solutions. Strong communication skills and the ability to translate complex insights for non-technical More ❯

data scientists to develop and productionise models Troubleshoot, debug, and refine model code Partner with cross-functional teams to translate business needs into data-driven solutions Essential skills: Python (pandas, NumPy, scikit-learn) – data wrangling, modelling, feature engineering SQL – querying structured datasets Model Development & Validation – classification, unsupervised learning (outlier detection), ranking models ML Deployment – containerised deployments (Podman, SageMaker, DSW pipelines 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 ❯

experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge of media More ❯

experience in a data science or analytics role, preferably within the AI/ML industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision More ❯

experience in a data science or analytics role, preferably within the AI/ML industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision More ❯

working in a collaborative, face-to-face, and iterative development environment. Skills & Experience Strong foundation in applied mathematics, statistics, or machine learning. Experience building and deploying models in Python (pandas, NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch More ❯

working in a collaborative, face-to-face, and iterative development environment. Skills & Experience Strong foundation in applied mathematics, statistics, or machine learning. Experience building and deploying models in Python (pandas, NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch More ❯

years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment Excellent communication and storytelling skills More ❯

in industry settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production environments To be successful in this role you must have hands … applied experience in machine learning and/or data science roles Solid understanding of MLOps and production deployment practices Experience with Python and core ML libraries (e.g., Scikit-learn, Pandas, PyTorch, TensorFlow) Familiarity with cloud platforms and data infrastructure (e.g., AWS/GCP/Azure, SQL, ELT tools) Understanding of ethical frameworks, explainability, and governance in AI Engaging & Adaptable Communication More ❯

tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯

tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯