Our client is a leading developer of clean energy technology, enabling the world’s most progressive companies to decarbonise at scale and pace. Their technology includes fuel cells for power generation and electrolysers for green hydrogen. Their licensing model has seen them establish partnerships with some of the world's most progressive companies to develop clean energy systems at the scale and pace needed to decarbonise power generation, transportation, industry, and everyday living.

Purpose Of The Role

You will be directly responsible for turning design verification requirements into executable test plans and deriving and reporting results from test data. You will bring expertise and prior experience to advise on the design of experiments and statistical confidence of test results and, where applicable, use machine learning to advance verification processes and optimise the operations and output of the Test Department. The role will directly support the development of its solid oxide technology by Identifying, developing, and implementing end-to-end applications of data science and machine learning techniques to optimise the operations of the Test Department. Extracting insights and improvements in data quality from test stand data as well as advancing the continuous validation of fuel cell stack models used for product development.

Key Accountabilities

Translate design verification and product validation requirements supplied by product development teams into executable test plans
Apply advanced statistical methods such as design of experiments and hypothesis testing to assess and optimise test plan design
Apply advanced data analysis and machine learning techniques to process test data and derive statistically sound test results
Advise the processes of design verification and product validation on best statistical practices and continuous improvement of the quality of test measurement data
Collaborate with the Data Analysis team to develop and maintain software tools and databases for test data analysis
Communicate test plans and test results to project teams in presentations and reports
Support the development of a business-wide cloud data management platform
Develop and deploy data visualisation tools (dashboards, apps) to ensure teams throughout the business have the information they need

Knowledge And Skills Required For The Role

Several year’s experience in the application of statistical methods in a product development and test environment
BSc or MSc in a quantitative field, such as statistics, Mathematics, Physics, or an Engineering discipline Knowledge of machine learning techniques and tools
Qualification or demonstrable knowledge in Six Sigma statistical techniques
Experience integrating different tools / applications to deliver a combined capability
Experience in Agile software development methodologies
Excellent written and oral communication skills Ideally knowledge and experience in Python and R Familiarity with methods to quantify and express measurement uncertainty
Experience with some of the following: MATLAB, Microsoft Azure, Databricks, and Power BI would be advantageous
Experience in a relevant sector, such as electrochemical products, power generation or automotive

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