2 of 2 Part-Time Time Series Analysis Jobs in the UK excluding London

complex industrial datasets where conventional big data approaches may not apply. In this role, you will be expected to apply data-driven methodologies to solve real-world problems using time series data and other imperfect or limited datasets. Candidates who thrive in ambiguity and take a hands-on approach to problem-solving will be well-suited for this … with clients and presenting technical insights to senior stakeholders. Exceptional communication skills are essential, particularly for conveying complex analytical findings to non-technical audiences. Key Responsibilities: Analysing and interpreting time series and real-time production data Deploying practical data science solutions to optimise processes Collaborating with stakeholders to define analytical problems and outcomes Presenting findings to executive … sites (up to three times per year, 2/3 days onsite) Essential Requirements: Demonstrable experience working with limited or imperfect datasets in an industrial setting Proven capability in time series analysis and process optimisation Strong interpersonal and communication skills, especially in client-facing environments Confidence in presenting analyses and recommendations to executive stakeholders Understanding of complex More ❯

environmental inputs to deliver intelligent, scalable and automated insights. The work carried out will directly drive operational efficiencies, reduce energy consumption and improve system reliability for customers. Perform statistical analysis and deep data interrogation across diverse datasets. Develop, test and deploy advanced analytics frameworks that uncover actionable insights. Design and implement end to end data science workflows. Translate R … D concepts and exploratory analysis into production ready algorithms and reusable components. Build machine learning models and design experiments to optimise building performance and asset control strategies. Select, apply and evaluate appropriate data science techniques (e.g., regression, classification, clustering, anomaly detection) based on the use case requirements. Work closely with internal teams to translate business needs into data led … working as a data scientist, preferably on client facing software solutions, within optimisation or energy focussed applications. Strong foundation in statistical techniques and machine learning, including regression, classification, clustering, time series analysis and pattern recognition. Degree in a quantitative discipline such as Applied Mathematics, Statistics, Computer Science, Engineering or Physics. Desirable MSc or PhD in a quantitative More ❯