1 to 25 of 238 Pandas Jobs in the UK excluding London

end technologies (React/Angular/Typescript) Exposure to Cloud platforms like Kubernetes/Cloud Foundry Proficient in coding in one or more languages and frameworks such as Python, Pandas, Django, Java, Spring, SQL, MQ/Kafka Demonstrated ability to problem-solve in real-time and handle technical issues with a sense of urgency. Strong communication skills and abilityto work More ❯

end technologies (React/Angular/Typescript) Exposure to Cloud platforms like Kubernetes/Cloud Foundry Proficient in coding in one or more languages and frameworks such as Python, Pandas, Django, Java, Spring, SQL, MQ/Kafka Demonstrated ability to problem-solve in real-time and handle technical issues with a sense of urgency. Strong communication skills and ability to More ❯

Snowflake, AWS, and Python Work directly with investment professionals to scope and deliver solutions What we’re looking for: Strong Python engineering skills, including use of data libraries like pandas and NumPy Experience working in front office environments Familiarity with data pipelines and cloud infrastructure Pragmatic, detail-oriented, and able to work independently Experienced Python-focused Software/Data Engineer More ❯

Snowflake, AWS, and Python Work directly with investment professionals to scope and deliver solutions What we’re looking for: Strong Python engineering skills, including use of data libraries like pandas and NumPy Experience working in front office environments Familiarity with data pipelines and cloud infrastructure Pragmatic, detail-oriented, and able to work independently Experienced Python-focused Software/Data Engineer More ❯

a bonus but not mandatory Desired Skills and Experience: Kafka and message bus/queue expertise Terraform and GitHub Actions skills Open Telemetry (OTEL) implementation Proficiency with NumPy and Pandas Systems integration experience Background in commodity trading (gas & power) Quantitative finance knowledge Understanding of compliance and regulation, particularly Sarbanes-Oxley (SOx) Role Responsibilities: Collaborate with both technical and business stakeholders More ❯

Please note that only applications with cover letters will be considered. Summary: digiLab is a pioneering AI company that helps enterprises transform complex challenges into innovation with uncertainty quantification, explainable AI and MLOps. Working with organisations in highly regulated or More ❯

utilising cloud platforms such as AWS, Azure and Snowflake for scalable deployment. Key Responsibilities: Develop and optimise quantitative models and analytical tools in Python Leverage statistical g packages (e.g., pandas, NumPy) for data analysis and modelling Work closely with portfolio managers, researchers, and technology teams to deploy robust, scalable solutions Design and implement data pipelines and workflows utilising AWS or More ❯

Python Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced More ❯

on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming and database querying. Overall knowledge of the Software Development Life Cycle. More ❯

Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt More ❯

Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt More ❯

interfaces for interaction with the models Testing and documentation Requirements: Experienced Python developer Experience utilising machine learning libraries such as (in order of importance) TensorFlow, HuggingFace, scikit-learn, PyTorch, Pandas, NumPy, SciPy Experience with AWS (principally EC2, S3, SageMaker) or Azure/GCP equivalents Some experience of designing, developing and deploying scalable infrastructure (eg Apache Airflow, Luigi or other cluster More ❯

approaches and frameworks such as RAG, LangChain, TensorFlow, and PyTorch. Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Proficiency in data pre-processing, data wrangling, and augmentation techniques. More ❯

the finance space. Requirements for the Senior Python Software Engineer position: MSc/PhD in a STEM discipline Strong Python development proficiency Experience with Python libraries such as NumPy, Pandas, Polars, etc. Bonus: Knowledge of financial markets or quantitative finance concepts If you are a Senior Python Software Engineer interested in joining an extremely talented development team, please apply to More ❯

one or more of the following database systems – DynamoDB, DocumentDB, MongoDB Demonstrated expertise in unit testing and tools – JUnit, Mockito, PyTest, Selenium. Strong working knowledge of the PyData stack – pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation. Experience with data analysis and troubleshooting data-related issues. Knowledge of design patterns and software architectures … one or more of the following database systems – DynamoDB, DocumentDB, MongoDB Demonstrated expertise in unit testing and tools – JUnit, Mockito, PyTest, Selenium. Strong working knowledge of the PyData stack – pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation. Experience with data analysis and troubleshooting data-related issues. Knowledge of design patterns and software architectures More ❯

years of hands-on experience. You’ll help streamline client onboarding, build robust integrations, and play a key role in evolving the platform. Tech Stack & Methodology Python (Dataclasses, Pandas, Asyncio) PostgreSQL, AWS (ECS, Lambda, SQS) Agile (XP), TDD, CI/CD, and strong automation culture If you're familiar with these tools—or eager to dive in—this is the More ❯

years in a leadership or senior role. Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data stack tools (e.g. More ❯

reshaping, and joining messy datasets using Python. Practical expertise and work experience with ML projects, both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering 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 ❯

issues in real-time, ensuring high availability and integrity. •3+ years of experience in data engineering, data architecture, or similar roles. •Expert proficiency in Python, including popular data libraries (Pandas, PySpark, NumPy, etc.). •Strong experience with AWS services—specifically S3, Redshift, Glue (Athena a plus). •Solid understanding of applied statistics. •Hands-on experience with large-scale datasets and More ❯

on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages. Overall knowledge of the Software Development More ❯

degree or a PhD with 5 years’ experience; or equivalent experience for Senior Software Engineer Recent experience in software development in modern Python Familiarity with data tooling (for example Pandas, Arrow, S3, etc) Familiarity with ML lifecycles and tooling (for example Pytorch, Huggingface, vllm, Airflow, Prefect, Luigi, etc) Ability to work with scientific software, either through experience or advanced degrees More ❯

on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages. Overall knowledge of the Software Development More ❯

and iterate on solutions. Requirements 1-4 years of experience in a quantitative, analytics, or developer role within a financial institution or trading environment. Strong proficiency in Python (e.g., Pandas, NumPy, Jupyter) and experience building data pipelines , analytical tools , or dashboards . SQL experience is a plus. Proficiency in Excel and data visualization platforms such as Power BI, Tableau, or More ❯

Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working More ❯