1 to 25 of 239 Pandas Jobs in England

Engineering, AI, or related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . 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 ❯

working with Quant Trading Technology, and/or working with real-time Low Latency Market Data . 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 ❯

working with Quant Trading Technology, and/or working with real-time Low Latency Market Data . 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 ❯

Front Office FX business and products (spot, forwards, options). Familiarity with data visualization tools (Altair Panopticon, Power BI, Tableau). Experience with Python and analytical libraries such as Pandas and NumPy. Clear communication, analytical mindset, and problem-solving ability. Education & Experience Master’s degree (or equivalent) in Computer Science , Mathematics , Physics , or Engineering . Proven experience (3–8 years More ❯

Front Office FX business and products (spot, forwards, options). Familiarity with data visualization tools (Altair Panopticon, Power BI, Tableau). Experience with Python and analytical libraries such as Pandas and NumPy. Clear communication, analytical mindset, and problem-solving ability. Education & Experience Master's degree (or equivalent) in Computer Science , Mathematics , Physics , or Engineering . Proven experience (3-8 years More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

alerting systems. Work closely with DevOps and infrastructure teams to deploy solutions in cloud and on-prem environments. Required Skills & Experience Strong proficiency in Python , including libraries such as Pandas, NumPy, and PySpark. Experience with data engineering tools (e.g., Airflow, Kafka, SQL, Parquet). Solid understanding of commodities markets , trading workflows, and financial instruments. Familiarity with cloud platforms (AWS, Azure More ❯

alerting systems. Work closely with DevOps and infrastructure teams to deploy solutions in cloud and on-prem environments. Required Skills & Experience Strong proficiency in Python , including libraries such as Pandas, NumPy, and PySpark. Experience with data engineering tools (e.g., Airflow, Kafka, SQL, Parquet). Solid understanding of commodities markets , trading workflows, and financial instruments. Familiarity with cloud platforms (AWS, Azure More ❯

frontend build tools Strong Linux and Git skills Desirable skills: AWS or cloud platform experience WebSocket and real-time data handling DevOps tooling (Docker, Kubernetes, Ansible) Data science packages (pandas, numpy, matplotlib) Modern C++ knowledge (C++17 and later) Interest in sports betting, financial services or trading platforms Benefits: Working alongside other extremely talented and driven engineers Extremely lucrative salary, bonus More ❯

IT and regulatory standards. Skills & Experience Strong proficiency in Python, with a focus on rapid prototyping and data driven applications. Solid understanding of multi-processing and AsyncIO. Experience with pandas, NumPy, and SQL for data analysis and transformation. Exposure to REST APIs, messaging systems, and integration with trading or risk platforms. Hands-on experience building Front End tools or GUIs. More ❯

and more on reliability and fixes. Key Skills: Investigating and debugging complex data flow and Machine Learning issues within a live, high impact production environment. Extensive Python, NumPy and Pandas is required for this role. You must demonstrate a deep commercial background in the following areas: Extensive Python: Very strong, production-level Python coding and debugging skills. Production Environment: Proven More ❯

alignment between technology initiatives and business objectives. Required Qualifications: 6+ years of experience in full stack software development. Proficiency in sever side Python programming. Proficiency in data analysis using Pandas, Numpy, SciPy etc. Experience with object oriented design, distributed systems architecture, performance tuning. Experience with designing and programming relational database such as MySQL, RedShift, Oracle SQL Server, or Postgres. Experience More ❯

processing and ML jobs, including the use of IAC to build data pipelines Expert knowledge of Python. An excellent knowledge of basic machine learning libraries, such as NumPy, SciPy, Pandas, Dask, PyTorch, Tensorflow, etc. A proven track record of linking data from multiple systems for scalable productionised solutions with security and monitoring best practices. Experienced with Cloud Security best practices. More ❯

OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

Manage cloud-based and on-prem setup Requirements: 25 years experience in ML engineering/MLOps roles Strong proficiency in Python and experience with relevant ML libraries/frameworks (pandas, numpy, sklearn, TensorFlow, PyTorch) Strong understanding and experience in implementing end-to-end ML pipelines (data, training, validation, serving) Experience with ML workflow orchestration tools (e.g., Airflow, Prefect, Kubeflow) and More ❯

scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯

scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯

experienced AI/Data Developer for an urgent contract assignment. Key Requirements: Proven background in AI and data development Strong proficiency in Python , including data-focused libraries such as Pandas, NumPy, and PySpark Hands-on experience with Apache Spark (PySpark preferred) Solid understanding of data management and processing pipelines Experience in algorithm development and graph data structures is advantageous Active More ❯

Mentor junior engineers and contribute to engineering best practices Required Skills & Experience: 5+ years of experience building and maintaining data pipelines in production environments Strong Python and SQL skills (Pandas, PySpark, query optimisation) Cloud experience (AWS preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed More ❯

with at least 3+ years leading data science teams. Fluent in Python and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas ) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression, classification More ❯

with at least 3+ years leading data science teams. Fluent in Python and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression, classification More ❯

and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯