Graduate Analytics Training Scheme - July Start
- Cumbria, North
- £24,000 YEAR
- 12th Sep ’22
- 72 days left!
This company is a provider of specialist analytics software solutions for clients. Their clients span a number of FTSE 100 companies across a range of industry sectors, including major high street banks and government institutions.
Graduate Analytics Training Scheme: Start date: Sept 26th 2022
- Do you love analytics and data? Have you used software such as Maple, Matlab, R, E-views, Minitab, Python, etc?
- Do you want to receive specific analytics training in a very in-demand analytics package?
If so this role could be for you!
This is an exciting opportunity to receive comprehensive SAS training over an intensive nine week period. Following the course, you will be deployed with one of their blue-chip clients working amongst other SAS professionals.
The client offers a superb working environment, an attractive salary (from day one of training) and an unparalleled level of training in SAS and systems analysis techniques. Their programme provides a unique opportunity to gain a competitive advantage over the rest of the graduate entry-level market.
Things To Consider:
- Training location: Cumbria - in person, classroom based training and then assigned to one client for 1-2 years. This will be a large town or city in the UK or remote working. You need to be prepared to relocate for this.
- Paid during training?: Yes!
- Other: MUST be prepared to relocate throughout the UK for this role although initially you can work remotely
- Salary: £24K, then reviewed and increased at regular intervals
- Interested in knowing more? Please get in touch with a copy of your CV for review
The company is looking for candidates who are self-driven, demonstrating strong analytical capabilities and excellent communication skills. The key to success is having a logical, inquisitive mind and an ability to apply knowledge to solve real-world problems.
Typically you will possess a degree demonstrating abilities in logic, analysis and data interpretation such as maths, statistics, economics, computing, engineering or a primary science subject. A minimum achievement of a 2:1 level degree, supported by A-level equivalents in complementary subjects or excellent A-levels in non-related subjects.