12 of 12 Pandas Jobs in the South West

senior client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version More ❯

science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), were using Azure in the team. Good SQL understanding in More ❯

science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), were using Azure in the team. Good SQL understanding in More ❯

systems (e.g. Red Hat, Ubuntu) Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus on: Design(Architecting, High-Level Design and Low-Level Design) Development Testing Deployment & Maintenance Experience of 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 ❯

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 ❯

not important, we do require the ability to become a fluent Python programmer in a short timeframe 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 ❯

not important, we do require the ability to become a fluent Python programmer in a short timeframe 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 ❯

in a senior data science or quantitative academic position Strong Python programming skills, with the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised learning More ❯

Data Scientist - Hybrid (Bristol-based) £40,000 - £45,000 (up to £50,000 for exceptional candidates) Hybrid Working | Python & Pandas Are you passionate about data and ready to make a real impact in the world of cyber risk? We're working with a forward-thinking company that's pioneering cyber risk modelling using advanced stochastic techniques, and they're on … and process efficiency. The work you do will directly influence insights into cyber exposure and risk trends. Key Responsibilities Clean, validate, and standardise large insurance datasets using Python (especially Pandas) Develop and refine internal tools and utilities for data cleaning workflows Support the integration of LLMs to automate data prep, including prompt engineering and model evaluation Generate insightful data reports … data science, reinsurance, and cyber risk What We're Looking For 2-4 years in a data-driven or technical role Strong Python skills with a deep understanding of Pandas Excellent attention to detail and a strong sense of data quality Commercial experience blending data engineering and data science approaches Experience with data ingestion and ETL pipelines Curious, adaptable, and More ❯

Scientist or Junior Data Scientist - Hybrid (Bristol-based 2-3 days a week) Insurance £40,000 - £45,000 (up to £50,000 for exceptional candidates) Strong skills in Python & Pandas with at least 2 years experience in a commercial Data Driven role Are you passionate about data and ready to make a real impact in the world of cyber risk … and process efficiency. The work you do will directly influence insights into cyber exposure and risk trends. Key Responsibilities Clean, validate, and standardise large insurance datasets using Python (especially Pandas) Develop and refine internal tools and utilities for data cleaning workflows Support the integration of LLMs to automate data prep, including prompt engineering and model evaluation Generate insightful data reports … of trends in data science, reinsurance, and cyber risk What We're Looking For 2-4 years in a data-driven or technical role Strong skills in Python and Pandas is a must Data ingestion using ETL pipelines experience A background in financial services is preferred, but not essential. Insurance experience a bonus Excellent attention to detail and a strong More ❯