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Data Scientist

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About us.

We’re The Very Group, home to Very.co.uk, Littlewoods.com and a team of 4,000 super-talented people.

We’re the UK’s largest integrated digital retailer and financial services provider, and we’ve been helping customers say yes when it matters most for over 100 years. In that time, we’ve consistently reinvented our business to adapt to economic conditions and industry changes – going from bricks, to clicks, to mobile.

But despite our passion for reinvention, we’ve never wavered from our purpose; to make good things easily accessible to more people. It means giving our customers the brands they love, an outstanding shopping experience and flexible ways to spread the cost.

We’ve continued to deliver for our customers throughout the Covid-19 outbreak – and we’ve done it by transforming the way we work.

We’re fired up for the future and the next stage in our development. We’ll give customers access to more great brands for themselves and their families, a seamless shopping experience and even more control of their finances through innovation in flexible ways to pay.


Opportunities in our Data Science community:

Our Data Science teams work across the business in a number of areas to help drive innovative, collaborative and iterative solutions to challenging problems. You will work closely with various business areas to drive insights, improve our products and create help more effective solutions. Typical Data Science projects may involve Experimentation, Marketing, Retail and Operations or Digital Product and CX. The key thing that all our teams do is support our business colleagues to make bold data driven decisions that drive value for our business and our customers.

What we do:

Data Science at The Very Group utilises advanced analytical techniques and statistical modelling to support many areas of the business and contribute to their success. This can range from working on how we measure and optimise our marketing spend, how we make stock purchasing decisions, to how do we diagnose the crucial customer challenges in our digital customer experience and make recommendations to improve them.

Some of our key wins recently have included:

  • The introduction of a new Digital Attribution report to help our marketing teams operate more effectively.
  • Successfully launched a suite of individual product recommendations within email communications
  • The adoption of a Quasi Experimentation methodology to provide teams with a greater level of understanding of the impact changes in marketing and financial products have on our customers
  • We launched a new methodology for analysing customer feedback as part of our NPS survey which helps us to diagnose customer problems more efficiently.
  • A successful internal hackathon where a number of colleagues from across the business joined forces to solve key data challenges.
  • Launched demand forecasting models to help make effective product planning and buying decisions.

These recent wins within the team highlight the importance of the function to the business. Demand for the team is always greater than what we can meet. Data is at the very heart of our business with board level visibility of many of the projects we work on.

How we work:

The Data Science team works with many different parts of our business, adopting working styles to best suit the collaboration. Our business is moving towards a Tribe and Product structures which provides our data science teams the opportunity to work closer to the business problem. The team champions innovation and a pioneering spirit for constant development. Our teams are empowered to work on complex projects and develop a strong culture of friendship and collaboration. We encourage our team members to feel part of the wider data community across the business.

What do we look for?

You will be an outcome driven data scientist, comfortable working as part of a wider team. You will have a proven ability to solve problems and establish working relationships with others. It is vitally important that you are eager to learn, to get involved and to work on a number of different challenges and business problems. The Very Group is an ever-changing place to work and being comfortable with change and embracing it as an opportunity to develop personally and professionally is crucial. Collaboration and knowledge sharing are vitally important and encouraged within the team.

Self-development is important for us. We see both learning together as a team through the process of delivery and individual learning to build specific skills to able to contribute more to the team, as important. We will give you the time and tools to do this.

Requirements

  • Ideally have a quantitative degree such as Computer Science, Mathematics or Science degree, though high relevant experience also acceptable.
  • Min of 2 years industry/business experience or further education (Masters/PhD).
  • Has a good theoretical command of a range of different models and analytical techniques.
  • Has a good practical knowledge of propensity modelling, recommendation algorithms or similar
  • Highly proficient in at least one framework (SAS, R or Python) with an ability to produce readable, well-structured reusable code. Able to demonstrate experience in data wrangling, cleaning and pre-processed data.
  • Has a good understanding of DS domain and workflow, informed from practical experience. Real life experience of working with data and understanding the trade-offs and challenges of data science work.
  • Eager to learn and develop technical skills – also happy to share knowledge with others.
  • A proven ability to solve problems, anticipate issues and challenges in data processes and able to find opportunities to improve processes and ways of working.
  • Has strong written and verbal communication. Able to take people on a journey with them. An ability to tailor your communications to non technical audiences is important.

Key Responsibilities

  • Working with key Marketing stakeholders to develop predictive models and/or algorithms to drive customer engagement, sales and ultimately profit
  • Working with technology team to build scalable solutions to allow easy deployment of developed models through a variety of different mechanisms such as Email, Push Notification and Website Messaging
  • Assisting in the design of tests to prove the value of models produced
  • Identifying opportunities to improve the quality of existing models and solutions through the addition of new data or application of alternative Data Science techniques
  • Guiding business how to ask the right questions to enable actionable strategic decisions, translating those questions into data science problems, choosing appropriate models to solve it.
  • Contributing to improving Data Science methodologies code base at The Very Group.
  • Building trust and credibility with stakeholders. Working in several different ways and team structures.
  • Defining problems, scoping and planning projects. Self-managing the delivery of objectives as part of a team. Proactively trying to solve blockers.

Benefits

  • Generous and competitive starting salary
  • Regular salary reviews and career progression
  • £1,000 of flexible benefits allowance (can take a part as salary uplift)
  • Bonus
  • Matched pension at 6%
  • 1x Life Assurance / Private Medical
  • Brand discount up to 25%
  • Cycle to work scheme
  • 30 days holiday + bank holidays
  • Free on-site gym
  • Discounted coffee houses and food outlets
  • Flexible Working


How to apply.

If you're interested to find out more please contact Jordan Barlow or Steven Williams in the talent acquisition team at The Very Group or apply online.

Please note that the talent acquisition team are managing this vacancy directly, and if successful in securing this position, you may be required to undertake a credit, CIFAS and CRB check.

We're an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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