Data Scientist

At Loaf we make insanely comfy sofas, beds and other laid-back wares that help people lead happier, more relaxed lives. And we're looking for our first in-house Data Scientist to join our Marketing team here at Loaf HQ.


This is an exciting, newly-created position with huge scope for growth and development. As Loaf's first in-house Data Scientist, you'll play a pivotal role in helping us realise our ambitious growth plans. We've recently invested a lot into developing our data architecture and we're now chomping at the bit to apply data science to our marketing, sales and customer data to generate deeper insights, more accurate forecasts and more effective recommendations.

You will use your data science wizardry to deliver analysis that will help the business better understand marketing effectiveness and to develop models that inform future campaign planning and strategies. You will use your brilliant communication skills to convey complex analysis and deliver actionable insight to the wider marketing team. And your innate curiosity will uncover fresh insights and unlock new opportunities that will help take the business to another level.

If you are a bright and hardworking Data Scientist with a passion for data who wants the opportunity to join a brilliant business on a mission to build something special, then we'd love to hear from you.

KEY RESPONSIBILITIES

  • Capture and refine requirements for marketing analysis and customer insight projects briefed in by the marketing, e-commerce and retail teams
  • Extract data from the data warehouse and employ analysis and modelling techniques in order to deliver on these requirements
  • Present analytical outputs to key stakeholders, taking complex information and communicating it as clear and actionable insights
  • Build, automate, monitor and improve analyses and models that support ongoing decision-making with a particular focus on marketing attribution, retail modelling, customer segmentation and lifetime value
  • Leverage your technical capabilities and innate curiosity to proactively identify opportunities to improve marketing and wider business performance

SKILLS, ATTRIBUTES & EXPERIENCE

You absolutely have to be or have the following:

  • An A-player Data Scientist with at least 5 years' experience using data science and predictive modelling to tackle business problems, ideally related to marketing
  • A talented student of mathematics and statistics with experience studying computer science a bonus calibre
  • A mastery of R, SQL with experience working with AWS. Knowledge of Linux environments would be ideal too
  • Exceptional problem-solving & logical thinking skills with an ability to innovatively deal with complex problems
  • A fusspot about detail with a relentless commitment to delivering outstanding work to agreed deadlines
  • An excellent communicator and an ability to connect and influence people across all areas of the business (so you need to be able to laugh at yourself!)
  • Always on the look-out to improve how things are done, challenging the status quo and never accepting second best
  • A self-starter who's happy working autonomously and under pressure in a fast-paced environment (we know, everyone says that!), bringing a positive vibe to work every day no matter what curve balls are thrown

And, most importantly of all, you absolutely must be an all-round good egg, with a real can-do willingness to get on with the job and make great things happen.

In return you can expect a forward-thinking, friendly bunch committed to building a fabulous company with brilliant people.

If you think you fit the bill then apply now with a covering letter explaining why you think you are the perfect Loafer plus a copy of your CV.

Regrettably, only successful candidates will be contacted. If you have not heard from us within 2-3 weeks, then unfortunately on this occasion you have not been successful.

At Loaf, we're working really hard to be inclusive. No matter what identity or background, we want everyone to feel welcome in a place where we can all be ourselves. We'd love you to join us on our journey.