About the Role

Whilst pockets of insight and analytics exist, building our analytical capabilities is a core pillar of Dyson's global data strategy. As more consumers engage with Dyson, owning more types of products, and across more markets, the volumes of data is now vast. Understanding how to use this data to improve everything from customer experiences, campaign development and retailer business planning will all be key to Dyson's success.

This role sits within the EMEA Business Intelligence & Analytics team and is tasked with leading the data science activities that support and enable data led decisions at both a Market and Region level. As a member of the Data Analytics team, you sit at the data source encouraged to define and deliver business analytics projects using data science modelling and statistical techniques to drive strategic decisions.

Through regular touch points with stakeholders, you will identify opportunities for new and improved analytics and work with our Business Intelligence and Business Analytics teams to bring those requirements to life. Key to the role is defining and delivering solutions that deliver tangible business benefits, informs critical business decisions as well as producing recommendations that enhance our operational efficiency. Understanding and aligning to department as well as market goals and strategy is at the centre of the role.

Responsibilities:

Own our data science roadmap working with our market colleagues to collaborate on priorities & delivery
Ensure that both the Markets and Region are supported and enabled with actionable insights and analytics
Capture clear requirements ensuring delivery to agreed timelines
Deliver prescriptive/predictive modelling and statistical analysis to support decision making
Develop and implement supporting processes to enhance and maintain our analytical capabilities
Proactive stakeholder management with focus on communication and enablement

Skills

Highly proficient in R/Python and SQL.
Experience using statistical and forecasting techniques such as time series analysis, forecast modelling, regression analysis etc.
Experience of gathering and interpreting business requirements
Develop and present analysis that is easy to understand and digest
Excellent communication skills building strong business relationships with key stakeholders
Ability to source and manipulate large /complex data sets from cloud storage and compute environments, Google Cloud Platform experience preferred
Significant applied commercial data science experience with data analytics capability
Experience with visualisation software a plus (e.g. Tableau, Looker)