Senior Data Scientist

About

The Role

National Energy System Operator (NESO) recognises the potential of bright and talented individuals, and we encourage you to join us as Great Britain’s energy system undergoes an ambitious, exciting, and vital transformation. Together with industry, we are creating a cleaner, more sustainable future.

We are looking for a Senior Data Scientist to join the Data Science team as part of Gas and Whole Energy Network Development. The team produces probabilistic forecasts and provides analytical insights as part of NESO’s gas network planning functions, and are growing in scope to support work around decarbonisation, hydrogen network planning, and whole energy interactions. The Senior Data Scientist will play a key role in developing, maintaining, and running models, and in driving change through delivering new data insights.

You will develop pipelines and automation for existing processes, and will lead the team in following data management and data quality best practice. You will provide technical leadership, driving the creation and improvement of data science techniques to ensure our modelling work remains robust. You will also provide input and challenge to steer the direction of a range of projects, taking a leading role in supporting the development of colleagues across NESO’s data science community.

• Working within established data handling guidelines, collect, collate, and cleanse raw data and convert into useable formats. Apply an end-to-end mindset, understanding both where the data has come from and how it can be used to drive meaningful decision support for the NESO leadership.
• Develop probabilistic forecasts of GB gas demand and supply at a regional level using a range of statistical techniques, including Monte Carlo sampling. Maintain and run models to support analysis feeding into the Centralised Strategic Network Plan.
• Use data science skills to support projects within the wider GWEND team concerning emerging hydrogen network planning, decarbonisation of industrial cluster sites, and whole energy interactions, including the analysis of geospatial data.
• Develop and maintain data pipelines for existing GWEND processes, and drive the automation of existing processes.
• Effectively communicate the impact of technical findings to a widespread audience, including Senior Management, Ofgem, DESNZ, and National Gas, ensuring insights are used to drive impact.
• Take a leading role in scoping out and planning data science projects, in response to emerging opportunities and business needs.
• Stay abreast of developments and advancements in data science, machine learning, automation, and other relevant trends to drive continuous improvements in how NESO manages and capitalises on the information and data it holds.
• Lead data quality and assurance, and data management processes within GWEND.
• Take a leading role in the emerging data science community throughout NESO, demonstrating best practice and supporting the development of other team members.
• Undertake ad hoc projects and initiatives relevant to data management, data handling, data cleansing, high-volume analytics, and insight generation as requested by NESO management. Undertake exploratory data analysis of complex data sets and develop data visualisations used to bring insight to a range of stakeholders.

Applicants must have the right to work in the UK by the start of employment. Visa sponsorship may not be available for this role and will be considered in line with business requirements.

• Has proven experience in writing clear and well-documented productionised code in R, Python, or another high-level language, which is used to drive business decisions.
• Has experience of developing statistical (and machine learning) forecasting models from first principles, and understanding of the strengths and limitations of modelling assumptions. Knowledge of statistical techniques, such as Monte Carlo methods, regression analysis, and clustering would be beneficial.
• Is adept at using version control and a cloud computing environment as part of a team of data scientists.
• Has experience of developing end-to-end data pipelines and…