Data scientist (Data Wrangler)

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You can find further details about the role, including key responsibilities and accountabilities, alongside the organisational structure and person specification in the attached Job Description and other supporting documents. 

Your application needs to show evidence of your competence in the following areas:

Analytics for impact

·       Apply a range of analytical techniques, in consultation with experts if appropriate, and with sensitivity to the limitations of the techniques.

·       Use expertise to propose techniques appropriate to business problem and characteristics of dataset.

·       Draw on expertise in several analytical techniques, including their theoretical basis and application.

·       Identify key messages from analytical work, translating these into terms for use with either technical or non-technical audiences.

·       Report on your own analytical work in sufficient detail, meeting customer needs, effectively presenting results in both written and oral form.

Professional delivery & innovation

·       Work with customers to understand their needs, create clear plans and setting priorities which meet the needs of both the customer and the business.

·       Deliver good customer service which balances quality and cost-effectiveness.

·       Identify areas of potential risk in own and others' work, selecting and using appropriate Quality Assurance methods and suggesting appropriate mitigation of risk.

·       Actively identify and take opportunities to promote data science to wider community.

·       Experiment with innovations, manage and learn from failures and shares lessons learned within the team.

·       Apply knowledge of new and evolving technologies, including open-source software, suggesting appropriate methods and techniques to incorporate in project work.

Engineering

·       Use data exploration techniques to understand the characteristics of a dataset, evaluate suitability for subsequent analysis and explain this to other analysts.

·       Apply data engineering standards and tools to create and maintain data pipelines.

·       Document and communicate the details of data structures to others.

·       Design, code, verify, test, document, amend and refactor moderately complex programs/scripts.

·       Collaborate in reviews of work with others as appropriate.

·       Proactively adopt practices that ensure rigorous and reproducible findings in development of analytical data products.

Leadership & collaboration

·       Understand how your work and the work of your team supports wider objectives and meets the diverse needs of stakeholders.

·       Focus on overall goals and not just specific tasks to meet priorities.

·       Show pride and passion for your work and positive, inclusive engagement with your team.

·       Contribute to an inclusive working environment where all opinions and challenges are listened to, and all individual needs are taken into account.

·       Change ways of working to aid cooperation within and between teams in order to achieve results.

·       Offer support and help to colleagues when in need, including consideration of your own and their wellbeing.

Applicants should use their supporting statement to demonstrate their proven ability across these four areas. Your application will be assessed against these four areas.