101 to 125 of 211 Pandas Jobs in England

Advanced programming skills in SQL, SAS (desired), Python, and the ability to write production-level code Familiarity with the most standard Python libraries used in ML (e.g., Scikit-Learn, Pandas, Numpy, LightGBM, XGBoost, just to name a few) Foster new and innovative machine-learning techniques and approaches General: Passionate for continuous learning, experimenting, and applying open-source technologies within the More ❯

interoperability between platforms is essential. Programming & Scripting : Knowledge of Python and Rust for pre- and post-processing tasks, prototyping, and interoperability with low-code solutions. Familiarity with MATLAB or Pandas/Polar for numerical computing and data analysis, particularly for processing workflows that require complex calculations. Database Management : Proficiency in SQL for database management (such as Microsoft SQL Server, MySQL More ❯

including Vertex Pipelines (or similar platforms). Technical Proficiency: in SQL and Python, along with familiarity with standard libraries used in data science such as scikit-learn, Keras, TensorFlow, pandas, NumPy, seaborn, and Matplotlib. Desirables: While not essential, the following experience would be highly beneficial: Production Experience with LLM Monitoring: Hands-on experience with monitoring LLMs in production, including familiarity More ❯

and methodologies About you We don't expect perfection, but for this senior role we are looking for someone with: Strong Python skills, particularly within the data science ecosystem (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, visualisation libraries) 4+ years of experience delivering machine learning products end-to-end in production Hands-on experience with LLMs - fine-tuning, prompt engineering More ❯

related to credit risk management. • 2+ years of experience as a quantitative researcher or data scientist. • Strong programming skills in Python and experience with data science tools such as Pandas, NumPy, and SciPy. • Strong statistical and modeling skills. • Strong communication and collaboration skills. • Experience in the energy industry is a plus. Competitive salary and a stock options sign-on bonus More ❯

with active SC will be prioritised) Within this role, you will be responsible for: Cleaning and processing tabular data (Excel, CSV, databases) Building data transformation pipelines using Python and pandas Writing SQL queries to extract and manipulate relational data Implementing data validation and quality assurance processes Working with JSON, XML, and CSV formats Supporting metadata cataloging and reference data management More ❯

with active SC will be prioritised) Within this role, you will be responsible for: Cleaning and processing tabular data (Excel, CSV, databases) Building data transformation pipelines using Python and pandas Writing SQL queries to extract and manipulate relational data Implementing data validation and quality assurance processes Working with JSON, XML, and CSV formats Supporting metadata cataloging and reference data management More ❯

and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication skills and a passion More ❯

Work with other data scientists to build and deploy production-level solutions Troubleshoot and debug code Work with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models More ❯

types and structures Unit testing using pytest Proficiency in SQL (we use MySQL, but experience with other SQL platforms is welcome). Experience with data manipulation and transformation using Pandas . Familiarity with ETL/ELT processes and data warehousing concepts. Understanding of cloud platforms (AWS or Azure). Basic knowledge of Git and GitHub for version control and collaboration. More ❯

types and structures Unit testing using pytest Proficiency in SQL (we use MySQL, but experience with other SQL platforms is welcome). Experience with data manipulation and transformation using Pandas . Familiarity with ETL/ELT processes and data warehousing concepts. Understanding of cloud platforms (AWS or Azure). Basic knowledge of Git and GitHub for version control and collaboration. More ❯

cross-functional environment with other data scientists, software engineers, and T&L domain experts Your professional experience Essential: Expert Python programmer proficient in frameworks/libraries such as: Numpy, Pandas, Scikit-Learn, Langchain, Llamaindex, Azure AI Foundry, among others Practical experience and deep expertise with GenAI techniques such as Finetuning, Prompt engineering, prompt orchestration, retrieval methods (RAG and Knowledge graph More ❯

Ideally experience with de novo transcriptome assembly, Machine Learning and/or Artificial Intelligence, or experience mining genomic data Experience with Python and libraries such as SciPy, Pytorch, NumPy, Pandas etc. What Next? If you'd like to hear more about this exciting Bioinformatician position, just give me a call or drop me an email, I'd love to chat More ❯

macro trading. Proficient in Python development, Devops, and Linux environments. Expert experience data pipeline development, specifically ETL/ELT pipelines. Familiarity with data analytics tools and libraries, such as Pandas and NumPy. Skilled with relational and non-relational database management. Ability and willingness to collaborate with traders and analysts in a real time environment. Strong analytical and problem-solving abilities. More ❯

experience in data science or a quantitative academic field. Strong programming skills, with the ability to quickly become fluent in Python. Deep knowledge of core data science libraries (NumPy, Pandas, Scikit-Learn) and at least one deep learning framework (TensorFlow, PyTorch, or similar). High mathematical and statistical competence, with the ability to design new algorithms when needed. Experience leading More ❯

accuracy. Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads More ❯

accuracy. Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads More ❯

Experience deploying and managing applications using Azure and Docker. Familiarity with frameworks such as LangChain and expertise in Retrieval-Augmented Generation (RAG) models for AI-driven applications. Proficiency with pandas for data manipulation. Full Stack Developer - What's in it for you? Salary Reviews: Twice a year to recognise your contributions. Generous Annual Leave: Enjoy 25 days plus three days More ❯

DB experience and Vector DB experience * Proven experience in time series analysis and forecasting, preferably in a commercial or industrial setting. * Strong proficiency in Python, including libraries such as Pandas, NumPy, and scikit-learn for data manipulation and modelling. * Experience with machine learning algorithms. * Proficient in data visualization techniques to effectively communicate insights from time series data. * Strong problem-solving More ❯

academic field Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯

and performance of a potential solution Comprehensive knowledge of software engineering, programming fundamentals and industry experience using Python Experience with data manipulation and processing, such as SQL, Cypher or Pandas A can-do proactive and assertive attitude - your manager believes in freedom and responsibility and helping you own what you do; you will excel best if this environment suits you More ❯

APIs, and managing databases. The requirements Essential: Python software engineering experience. SQL experience. Happy working in an unstructured, dynamic, and autonomous environment. Bonus: Mastery of SQL, Alchemy, scikit-learn, pandas, and PostgreSQL. Experience designing, building, and managing relational databases. Strong numerate background, i.e. maths, physics, comp-sci, engineering, etc. DevOps exposure: i.e. containerization, continuous integration/deployment (CI/CD More ❯

academic field Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯

We are looking for individuals who have working experience in or are comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms More ❯

We are looking for individuals who have working experience in or are comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms More ❯