19 of 19 Remote Pandas Jobs in the West Midlands

ML models into production. Prior experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps More ❯

ML models into production. Prior experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps More ❯

ML models into production. Prior experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps More ❯

ML models into production. Prior experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps More ❯

ML models into production. Prior experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps More ❯

and building reusable analytical datasets. Modern BI: hands-on experience with a modern BI platform with integrated semantic layer (e.g Omni, Looker, Thoughtspot) Python for analysis: practical experience with pandas/numpy and notebook-based workflows for LTV, attribution, simulations and experimentation analysis. Domain expertise: deep, practical knowledge in one or more of the following functions & platforms: CRM (e.g. SalesForce More ❯

and building reusable analytical datasets. Modern BI: hands-on experience with a modern BI platform with integrated semantic layer (e.g Omni, Looker, Thoughtspot) Python for analysis: practical experience with pandas/numpy and notebook-based workflows for LTV, attribution, simulations and experimentation analysis. Domain expertise: deep, practical knowledge in one or more of the following functions & platforms: CRM (e.g. SalesForce More ❯

and building reusable analytical datasets. Modern BI: hands-on experience with a modern BI platform with integrated semantic layer (e.g Omni, Looker, Thoughtspot) Python for analysis: practical experience with pandas/numpy and notebook-based workflows for LTV, attribution, simulations and experimentation analysis. Domain expertise: deep, practical knowledge in one or more of the following functions & platforms: CRM (e.g. SalesForce More ❯

and building reusable analytical datasets. Modern BI: hands-on experience with a modern BI platform with integrated semantic layer (e.g Omni, Looker, Thoughtspot) Python for analysis: practical experience with pandas/numpy and notebook-based workflows for LTV, attribution, simulations and experimentation analysis. Domain expertise: deep, practical knowledge in one or more of the following functions & platforms: CRM (e.g. SalesForce More ❯

and building reusable analytical datasets. Modern BI: hands-on experience with a modern BI platform with integrated semantic layer (e.g Omni, Looker, Thoughtspot) Python for analysis: practical experience with pandas/numpy and notebook-based workflows for LTV, attribution, simulations and experimentation analysis. Domain expertise: deep, practical knowledge in one or more of the following functions & platforms: CRM (e.g. SalesForce More ❯

and building reusable analytical datasets. Modern BI: hands-on experience with a modern BI platform with integrated semantic layer (e.g Omni, Looker, Thoughtspot) Python for analysis: practical experience with pandas/numpy and notebook-based workflows for LTV, attribution, simulations and experimentation analysis. Domain expertise: deep, practical knowledge in one or more of the following functions & platforms: CRM (e.g. SalesForce More ❯

design, rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable More ❯

design, rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable More ❯

design, rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable More ❯

design, rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable More ❯

design, rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable More ❯

design, rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable More ❯

design, rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable More ❯

Intel AI tools an advantage. Digital Support/IT Support: Windows/macOS, O365/M365, ticketing, troubleshooting, networking basics, hardware/peripherals, customer service. Data: Excel, SQL, Python (Pandas), data cleaning, visualisation, basic analytics; Power BI/Tableau a plus. Confident online facilitator with excellent communication and pacing; able to engage beginners and upskill returners. Prior teaching/training More ❯