1 to 25 of 40 Pandas Jobs in the UK excluding London

data validation processes Ensure integration with internal data sources and reporting tools Required Skills 5+ years of Python development experience, ideally in financial services or commodities Strong proficiency in Pandas , NumPy , and time-series data manipulation Proven experience with FastAPI or Flask Familiarity with large datasets and real-time data pipelines Excellent debugging, profiling, and performance optimization skills Strong communication 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 ❯

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 ❯

workstreams to elevate team capability. Essential Skills & Experience Proven experience in analytics engineering , data engineering , or model development roles. Advanced proficiency in Python (including libraries such as NumPy and Pandas) and SQL . Demonstrated ability to deliver production-ready solutions in a commercial environment. Strong communication skills with the ability to engage stakeholders and translate technical work into business outcomes. More ❯

sorting, data filtering, pivot tables, vlookup, SUMIF/SUMIFS, charts. BI tools. Desirable PowerBI A/B testing. Split principles, test planning, logging. Desirable hard skills Python. Data analysis, pandas, numpy, scipy, statsmodels, seaborn, matplotlib etc. ETL processes. Airflow, Pentaho etc. IT understanding. Client-server processes. API. Back-end and front-end. Parsing. Algorithms and data structures. Management. Sprints, AGILE. 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 ❯

to write ad-hoc and complex queries to perform data analysis. Databricks experience is essential. Experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. You will be able to develop solutions in a hybrid data environment (on-Prem and Cloud). You must be able to collaborate seamlessly across diverse technical More ❯

to write ad-hoc and complex queries to perform data analysis. Databricks experience is essential. Experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. You will be able to develop solutions in a hybrid data environment (on-Prem and Cloud). You must be able to collaborate seamlessly across diverse technical More ❯

My Energy Trading client are looking for a Quantitative Python Developer to join their team.The role will be working within a LNG, Power, Gas team.Requirements: Python Development Libraries - Pandas, Numpy, SciPy Preference for multiple language (C#, C++, Rust, Java) Quantitative development. Commodities experience, LNG, Gas, Power would be a bonus. An understanding of DevOps, specifically Azure cloud experience would be More ❯

Services - Mandatory Good understanding of quantitative finance Good experience developing and optimising Python-based calculators and models. Strong experience developing high-performance APIs using Flask or FastAPI. Expertise in Pandas, NumPy and other computing libraries. Strong experience liaising with front-office stakeholders What you'll get in return Initial 6-month contract with extensions Up to £700pd umbrella London-based More ❯

Object Detection, LLMs, and frameworks such as Transformers (Hugging Face), PyTorch, OpenCV, YOLO. Programming: Strong Python (3.9+) skills, including OOP, async patterns, data structures, debugging. Data Processing: Proficient with Pandas, NumPy, SQLAlchemy/psycopg2, AWS Boto3. Cloud & Infrastructure: Hands-on AWS (Lambda, S3, CloudWatch, IAM, CDK, SQS, EKS/ECS/Kubernetes). API Development: FastAPI, REST API design, external More ❯

ML technologies: OCR, Object Detection, LLMs Libraries: Transformers/Hugging Face, PyTorch, OpenCV, PIL/Pillow, YOLO Python 3.9+ with OOP, async/await, and debugging techniques Data tools: Pandas, NumPy, SQLAlchemy/psycopg2 AWS: Lambda, S3, CloudWatch, IAM, CDK, SQS, EKS/ECS API development: FastAPI, Requests, JWT/OAuthDevelopment Practices Agile methodologies (Scrum/Kanban), XP techniques (TDD More ❯

ML technologies: OCR, Object Detection, LLMs Libraries: Transformers/Hugging Face, PyTorch, OpenCV, PIL/Pillow, YOLO Python 3.9+ with OOP, async/await, and debugging techniques Data tools: Pandas, NumPy, SQLAlchemy/psycopg2 AWS: Lambda, S3, CloudWatch, IAM, CDK, SQS, EKS/ECS API development: FastAPI, Requests, JWT/OAuth Development Practices Agile methodologies (Scrum/Kanban), XP techniques More ❯

a sales & trading environment (market data, order/execution data). Data wrangling: Hands-on experience with large datasets, time-series data, and advanced analytics. Programming: Proficiency in Python (Pandas) and Q/KDB+. Visualisation: Strong Tableau skills-able to turn complex data into actionable dashboards. SQL mastery: Advanced SQL skills; Impala experience is a plus. BI modelling: Experience designing More ❯

needs. Communicate technical concepts clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and More ❯

needs. Communicate technical concepts clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and More ❯

AI requirements into scalable solutions. Essential Experience & Skills 5+ years' engineering experience, with at least 3 years in ML Ops, Data Engineering, or AI infrastructure. Strong Python engineering skills (Pandas, Numpy, Jupyter, FastAPI, SQLAlchemy). Expertise in AWS services (certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face 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 ❯

skills. Bonus skills • Experience deploying and managing applications with Azure and Docker. • Familiarity with frameworks like LangChain and Retrieval-Augmented Generation (RAG) models for AI-driven applications. • Experience with pandas for data manipulation. What’s on offer • Regular salary reviews recognising performance and contribution. • Generous annual leave: 25 days plus three days over Christmas. • Flexible hybrid working to support work 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 ❯

async/await patterns * Data structures and algorithms for efficient data processing and model optimisation * Error handling and debugging using try-catch blocks, logging, and debugging tools Data Processing: * Pandas and NumPy for data manipulation, cleaning, and numerical operations * SQLAlchemy or psycopg2 for database connectivity and ORM operations * Boto3 for AWS service integration and automation AWS (working within Technical Lead More ❯

async/await patterns * Data structures and algorithms for efficient data processing and model optimisation * Error handling and debugging using try-catch blocks, logging, and debugging tools Data Processing: * Pandas and NumPy for data manipulation, cleaning, and numerical operations * SQLAlchemy or psycopg2 for database connectivity and ORM operations * Boto3 for AWS service integration and automation AWS (working within Technical Lead 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 ❯

and refining them to strong results. Experienced in engaging with non-technical stakeholders 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. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain More ❯

in the Natural Language domain or when working with other unstructured data. • Solid understanding of Python, including writing modular Pythonic code, familiarity with core Python data structures, fluency with pandas, and experience with unit testing. • Experience managing and mentoring junior colleagues. • Experience with chatbots and working with chat data. And any experience of these would be really useful: • Hands-on More ❯