76 to 100 of 224 Pandas Jobs in England

trading constraints. Automate Data Pipelines, designing and managing workflows for collecting, cleaning, and storing large volumes of financial data (e.g., price, volume, fundamentals, alternative data), often using tools like Pandas, NumPy, and Dask. Collaborate Across Teams for Deployment, working with researchers, traders, and DevOps teams to integrate Python models into production environments (e.g., through APIs, microservices, or containerized systems like More ❯

basic AI algorithms and explore practical applications of AI. Overview of AI and Machine Learning Types of machine learning (supervised, unsupervised, reinforcement) Introduction to Python Libraries for AI - NumPy, Pandas, Matplotlib Scikit-learn for machine learning Building AI Models Data preprocessing Training and evaluating models Advanced Programming for AI Integration This programme aims to equip participants with the knowledge and More ❯

version control processes. Stay up to date with advances in quantitative finance, computational techniques, and emerging technologies. Profile Strong programming experience in Python, C++, or C#; knowledge of NumPy, Pandas, and QuantLib advantageous. Solid understanding of mathematics, statistics, and numerical methods - including stochastic calculus, Monte Carlo simulation, and optimisation. Familiarity with derivatives pricing, risk metrics, and financial instruments across asset More ❯

a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions Excellent teamwork and More ❯

a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions Excellent teamwork and More ❯

of RESTful APIs as well as experience working with both synchronous and asynchronous endpoints Experience with Snowflake or Redshift with a strong understanding of SQL. Proficient in Python and Pandas Experience working with JSON and XML Strong understanding of cloud computing concepts and services (AWS preferably) Experience with Git or equivalent version control systems and CI/CD pipelines. Familiarity More ❯

of RESTful APIs as well as experience working with both synchronous and asynchronous endpoints Experience with Snowflake or Redshift with a strong understanding of SQL. Proficient in Python and Pandas Experience working with JSON and XML Strong understanding of cloud computing concepts and services (AWS preferably) Experience with Git or equivalent version control systems and CI/CD pipelines. Familiarity More ❯

insights. Skills & Experience: Essential - Demonstrable experience in Machine Learning, NLP, and GenAI including LLM/SLM fine-tuning and prompt development. Proficiency in Python and data libraries such as Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow. Practical knowledge in SQL/NoSQL databases and API development/integration. Proven ability to analyze model performance and optimize for accuracy, efficiency, and More ❯

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

master’s degree in a STEM subject (Mathematics, Computer Science or Engineering) Experience working in a data science or consulting role In-depth experience of working with Python and Pandas An entrepreneurial spirit and drive to work in an early stage start-up A curious mindset to understand how we can improve things and better help our clients address commercial More ❯

data cycle. Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD Coding experience in Apache Spark, Iceberg or Python (Pandas) Experience in change and release management. Experience in Database Warehouse design and data modelling Experience managing Data Migration projects. Cloud data platform development and deployment. Experience of performance tuning in More ❯

learning and cutting edge AI & Agents, honed through extensive practical experience across a range of domains Expert-level proficiency in Python and its data science ecosystem (e.g., scikit-learn, pandas), with the ability to select the right tools for complex problems and set technical standards for the team Advanced, hands-on expertise in SQL and big data platformslike Databricks, used More ❯

Stack Data Scientist, with a track record of taking ML projects from conception to deployment in a cloud environment (AWS preferred). Strong proficiency in Python for data science (Pandas, NumPy, Scikit-learn) and SQL (PostgreSQL is a plus). Hands-on experience with the full data lifecycle: data ingestion (e.g., web-scraping with BeautifulSoup, Scrapy, or Selenium), data wrangling More ❯

quantification, model evaluation, and statistical inference is highly valued. Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data More ❯

quantification, model evaluation, and statistical inference is highly valued. Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data 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 ❯

data cycle. - Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD - Coding experience in Apache Spark, Iceberg or Python (Pandas) - Experience in change and release management. - Experience in Database Warehouse design and data modelling - Experience managing Data Migration projects. - Cloud data platform development and deployment. - Experience of performance tuning in More ❯

Load Balancing. • CI/CD & DevOps Integration. • AWS (ECS, fargate , EC2, SNS, SQS, Cloudwatch, EKS, Kubernetes). Desirable skills/knowledge/experience: • Familiarity with data analysis libraries like Pandas, NumPy, and Scikit-learn. • Knowledge of data science and machine learning concepts and tools. Good to have: • Strategic thinking and problem-solving. • Collaboration and teamwork. • Effective communication and stakeholder management. More ❯

large, complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯

science ecosystem, ensuring data quality, building analytical pipelines, and visualising insights for stakeholders. 💰 Up to £600/Day Outside IR35 📑 6 months rolling contract 📍 Remote, LDN ♻️ Data Scientist - Python, Pandas, NumPy, Git, and Azure/AWS Key Responsibilities: Partner with cross-functional teams to translate business pain points into scalable data science solutions. Architect and deploy ML models (with a More ❯

science ecosystem, ensuring data quality, building analytical pipelines, and visualising insights for stakeholders. 💰 Up to £600/Day Outside IR35 📑 6 months rolling contract 📍 Remote, LDN ♻️ Data Scientist - Python, Pandas, NumPy, Git, and Azure/AWS Key Responsibilities: Partner with cross-functional teams to translate business pain points into scalable data science solutions. Architect and deploy ML models (with a More ❯

large, complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯

science ecosystem, ensuring data quality, building analytical pipelines, and visualising insights for stakeholders. 💰 Up to £600/Day Outside IR35 📑 6 months rolling contract 📍 Remote, LDN ♻️ Data Scientist - Python, Pandas, NumPy, Git, and Azure/AWS Key Responsibilities: Partner with cross-functional teams to translate business pain points into scalable data science solutions. Architect and deploy ML models (with a More ❯

science ecosystem, ensuring data quality, building analytical pipelines, and visualising insights for stakeholders. 💰 Up to £600/Day Outside IR35 📑 6 months rolling contract 📍 Remote, LDN ♻️ Data Scientist - Python, Pandas, NumPy, Git, and Azure/AWS Key Responsibilities: Partner with cross-functional teams to translate business pain points into scalable data science solutions. Architect and deploy ML models (with a More ❯