We are currently seeking a Data Analyst to join of the UK’s leading data solutions companies.
- Paying up to £60k.
- Offered on a hybrid basis, onsite 3 days per week, central London office.
This is a newly created role due to the exponential growth of their business and the recent acquisition of one of their competitors. This means that they can offer huge opportunities for progression, tailored specifically to your ambitions – tell them what you want to achieve, and they will work with you to accomplish this.
They work with a variety of nationally and internationally respected organisations within the utilities, telecoms, insurance, and banking sectors. As a business, they seek to resolve some of the core problems that exist for their clients – optimise value, improve revenue, and reduce debt. And so, they create bespoke products and services that join the dots between data, processes, policies, and systems.
They are a purpose-led company that prioritises principles over profit and that makes them a highly desirable place to work.
They have been publicly recognised for the industry-beating levels of client and employer satisfaction they provide to both employees and clients.
As a Data Analyst, you will:
- Turn large quantities of complex data into insights that will aid informed decision-making.
- You’ll produce data visualisations and detailed reports underpinned with clear business commentary.
- You’ll conduct consumer data analytics for their clients that will provide insights into a range of specific focus areas including (but not limited to) discount/promotion activities, customer eligibility compliance, and key performance indicator construction.
- Translate data analysis into targeted information which can be transformed into actionable improvements based on the specific client and/or industry need.
Essential skills required:
- 3+ years experience as a Data Analyst.
- Credit Risk, VBM, Revenue Assurance, data cleansing experience.
Desirable skills required:
- Strong applied technical and analytical skills using SQL and Excel.
- Experience using Python, R, or statistical modelling.