Universal Credit programme seeks lead data scientist
DWP offers £84,000 in bid to recruit senior data professional
The Department for Work and Pensions is offering an annual salary of up to £84,000 in its bid to recruit a lead data scientist for the Universal Credit programme.
The successful candidate will be tasked with ensuring “the quality and consistency of analytics-driven initiatives inspired by the UC programme”. Each of these initiatives will represent a multimillion-pound programme of work, the department said.
Additionally, the data science leader will be expected to cultivate relationships with peers across the DWP and the rest of government, as well working to grow the “data science, machine learning and AI capabilities” of the civil service.
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“As the lead data scientist embedded in the Universal Credit programme, you will be responsible for leading a high-performing function that delivers proactive, innovative and insightful data products within agile principles that tangibly improve the outcomes for millions of citizens across the country,” the DWP said. “In addition, you will play a prominent leadership role across the department for data and analytics driving a culture of continuous improvement and evidence-based decision making.”
Core areas of technical expertise required for the post include data visualisation and governance, coding, product development, and project management.
Applications are open until 15 July, with candidates asked to include in their submission a statement of no more than 250 words covering their credentials in certain stipulated “behaviours” and technology skills.
The statement must cover four types of behaviour: “seeing the big picture; changing and improving; working together; [and] leadership”. The technical skills that need to be addressed are: “data analysis and synthesis; communicating analysis and insight; [and] organisation capability development”.
Once applications have been sifted, successful candidates will be asked to attend DWP offices an make an impromptu presentation on a previously unseen topic, followed by a face-to-face interview.
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