1 to 25 of 67 Pandas Jobs in London

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

techniques or at least eager to learn them quickly. Python and Data Structure: You should be proficient in Python programming not just using standard python packages such as NumPy, Pandas, scikit-learn etc, but also familiar with data structure and algorithms, time and space complexity. Desirable Skills and Experience Experience with Agentic Frameworks such as LangGraph etc. Understand and having 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 ❯

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 ❯

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 ❯

scalable workflows. Help grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms 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 ❯

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 ❯