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Senior Analyst

  • Location: Accrington
  • Salary: Negotiable per year
  • Job Type:Permanent

Posted 12 days ago

  • Sector: Marketing
  • Contact: Shauna Penistone
  • Contact Email:
  • Expiry Date: 25 December 2021
  • Job Ref: 2948_1637840082

A well-known retailer with a turnover of £500 million per year are currently undergoing an exciting transformation in their data department. It's a perfect opportunity for a numerate graduate who is looking to build a career in a business with a fantastic culture. You'll be working with customer data, unearthing interesting insights in their behaviour to improve marketing campaigns and business processes. It's an exciting time to be joining due to the amount of investment in their data division, with rapid expansion on the cards in the future so progression is highly likely.

You will also benefit from:

  • An industry renowned, personalised training plan, which involves 1:1 mentoring from a team of analysts as well as external courses
  • A competitive salary (up to £27,000 with regular salary reviews thereafter)
  • Free parking and an onsite canteen
  • Generous annual leave and pension scheme
  • Generous staff discount on their wide range of products (including home, clothing, electricals, jewellery and health & beauty)
  • Corporate Gym membership
  • An award-winning culture with enormous growth in their digital sector, so you can naturally grow and progress with this division of the business

We are looking for applicants with the following background:

  • A degree in Maths, Computer Science, Statistics, Economics or related subject
  • Strong presentation skills (verbal and written)
  • Experience with SQL, Python, Power BI or related technologies would be hugely beneficial
  • Enthusiastic, willingness to learn and positive attitude
  • Inquisitive nature
  • Ability to build trust and rapport with business users

If this sounds like you, I'd love to hear from you!

Keywords: graduate analyst, data insight, power bi, business degree, maths, junior, program, SQL, Python, Power BI