176 to 200 of 245 Pandas Jobs in England

reports and concise business narratives Contributing to simple, reliable data pipelines and automated quality checks About You Minimum 1 year of commercial Data Science experience Strong hands-on Python (pandas, NumPy, scikit-learn) and SQL Sound understanding of statistics and forecasting Confident communicator - able to explain technical work clearly to non-technical audiences Why Apply Opportunity to build from scratch More ❯

experience. Skills & Experience: Strong hands-on experience deploying ML models in production environments. Excellent programming skills in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa More ❯

experience. Skills & Experience: Strong hands-on experience deploying ML models in production environments. Excellent programming skills in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa More ❯

and automation into data workflows, unlocking even more potential from their datasets. Skills & Experience Strong Python experience Experience with a web framework – Flask, FastAPI, Django , etc. Solid understanding of Pandas/NumPy for data manipulation SQL Server experience Experience building or maintaining web scraping tools to collect and structure data from online sources Who this role is great for Early More ❯

models to production Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or Engineering - or equivalent Proficiency in Python and relevant data science libraries (NumPy, pandas, scikit-learn etc.) Experience with SQL, Power BI, Git & GitHub Strong knowledge of Machine Learning Algorithms and respective theory Ability to work within a team, collaborating effectively with colleagues Strong More ❯

re Looking For You’ve led the delivery of applied machine learning projects, ideally across commercial or regulated sectors Strong Python skills and comfort using core libraries (e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI based More ❯

re Looking For You’ve led the delivery of applied machine learning projects, ideally across commercial or regulated sectors Strong Python skills and comfort using core libraries (e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI based More ❯

key strategic initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge More ❯

key strategic initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge More ❯

Who You’ll Be An experienced Python developer with strong knowledge of data structures, algorithms, and CI/CD pipelines. A Machine Learning professional skilled in data wrangling (SQL, pandas, NumPy), supervised and unsupervised learning, model evaluation, and feature engineering. Knowledgeable in Deep Learning frameworks such as PyTorch, with experience in neural networks and NLP models; exposure to generative and More ❯

Who You’ll Be An experienced Python developer with strong knowledge of data structures, algorithms, and CI/CD pipelines. A Machine Learning professional skilled in data wrangling (SQL, pandas, NumPy), supervised and unsupervised learning, model evaluation, and feature engineering. Knowledgeable in Deep Learning frameworks such as PyTorch, with experience in neural networks and NLP models; exposure to generative and More ❯

Who You’ll Be An experienced Python developer with strong knowledge of data structures, algorithms, and CI/CD pipelines. A Machine Learning professional skilled in data wrangling (SQL, pandas, NumPy), supervised and unsupervised learning, model evaluation, and feature engineering. Knowledgeable in Deep Learning frameworks such as PyTorch, with experience in neural networks and NLP models; exposure to generative and More ❯

and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or More ❯

and T&L domain experts Required Skills/Experience The ideal candidate will have the following: Be an expert Python programmer proficient in frameworks/libraries such as: Numpy, Pandas, Scikit-Learn, Langchain, Llamaindex, Azure AI Foundry amongst others. Must have Azure and be an expert with R&D on generative AI techniques Practical experience with GenAI techniques such as More ❯

and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or More ❯

Data Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g. More ❯

model performance. What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ More ❯

eCommerce: Google Analytics, conversion optimisation Skills & Experience Essential Strong SQL proficiency for data extraction and transformation Advanced Excel (pivot tables, VLOOKUPs, formulas) Power BI or Tableau experience Python familiarity (pandas, numpy) Proven data or BI role background Experience with large, complex datasets History of delivering practical insights Strong communication skills Desirable Wholesale/distribution/supply chain experience ERP systems More ❯

understanding of probability, statistics, and linear algebra, with the ability to apply these concepts to real-world problems. Extensive proficiency in Python, including mastery of libraries like scikit-learn, pandas, seaborn, and matplotlib. Significant experience writing and optimising complex SQL queries for data retrieval and manipulation in large-scale databases. Strong experience of Azure Data Stack (Databricks/Data Factory More ❯

and have in-depth knowledge of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment : DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud: You have worked More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using More ❯

AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using More ❯