1 to 25 of 132 Permanent Pandas Jobs in London

for efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity More ❯

for efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity More ❯

for efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity More ❯

for efficiency. Enhance and create advanced data visualisation applications. Requirements: Proficient in Software Python Development. 3-5 years experience in software engineering Experience with libraries/frameworks such as Pandas, Numpy, Scipy, etc. Skilled in data pipeline orchestration management libraries (e.g., Airflow, Prefect). Experience with cloud infrastructure (AWS, GCP, Azure). DevOps skills (CI/CD, containerisation). Familiarity More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and 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 ❯

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 ❯

manipulation, asynchronous programming, and performance optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working More ❯

manipulation, asynchronous programming, and performance optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working More ❯

manipulation, asynchronous programming, and performance optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working More ❯

manipulation, asynchronous programming, and performance optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful APIs, microservices, and working More ❯

rapid MVP development and iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification More ❯

rapid MVP development and iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification More ❯

or related field (or equivalent experience) 3-5 years of experience in data engineering (healthcare/medical devices preferred but not required) Strong Python programming and data engineering skills (Pandas, PySpark, Dask) Proficiency with databases (SQL/NoSQL), ETL processes, and modern data frameworks (Apache Spark, Airflow, Kafka) Solid experience with cloud platforms (AWS, GCP, or Azure) and CI/ More ❯

Azure ). Experience in applying statistical and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin More ❯

Azure ). Experience in applying statistical and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin More ❯

residence. Proficient in designing, developing, and maintaining RESTful APIs for data services using Python frameworks such as FastAPI, Flask, or Django. Strong experience with Python's data ecosystem (e.g., Pandas, NumPy) and deep expertise in SQL for building robust data extraction, transformation, and analysis pipelines. Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, or Snowflake More ❯

science solutions, defining minimum viable products (MVPs) and iterating based on user needs Person specification We're interested in people who have: python expertise : strong experience with core libraries (pandas, numpy, scikit-learn) and writing clear, modular, reusable code with error handling and logging data visualisation : ability to build interactive dashboards and reports using tools such as Plotly, Dash, Matplotlib More ❯

etc. as well as hands on experience on AWS services like SageMaker and Bedrock, and programming skills such as Python, R, SQL, Java, Julia, Scala, Spark/Numpy/Pandas/scikit, JavaScript Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience More ❯