Apprenticeships Audit - Data Analytics Degree Apprenticeship Leeds Autumn 2023 Leeds, England
Job description
Job details
Location: Leeds
Capability: Audit
Experience Level: Apprenticeships
Type: Full Time
Service Line: Audit - Data Analytics Degree Apprenticeship
Job description
In the Clara Analytics team, we bring together our deep industry knowledge with leading analytics expertise to harness the power of data; working with the largest global organisations to automate the Audit process. Data provides valuable insights which enable organisations to make better decisions. Analytics projects involve extracting, analysing and visualising data to support audit engagements. Our work has the power to transform the businesses we work with, providing them with deep insights which can help them to increase their revenue, reduce costs and manage emerging risks and future opportunities.
As a Data & Analytics degree apprentice, you’ll work towards a BSc (Hons) Digital and Technology Solutions qualification, providing you with the knowledge and skills to be an effective Audit analyst. You'll have the resources and support you need to learn how to understand object oriented programming as a concept, design and build databases, understand common system vulnerabilities and implement predictive modelling.
From the start, you'll be working on complex projects alongside some of the brightest minds in business and benefit from learning every day. There could be opportunities to get involved in areas such as product development and innovation activities, to ensure that KPMG’s analytics capability remains market leading on a global scale.
It’s challenging but rewarding. There's a real sense of community across Our KPMG – we're collaborative and value the different perspectives and ideas that contribute to our shared goal of delivering quality work. Once you join the programme, you’ll be working with our market leading technology experts on a variety of exciting projects. You’ll join an environment where you can come as you are, and supported to be at your best.
At KPMG, work is no longer a place we go, it's a contribution we make. Our people have always worked flexibly – so this way of working isn't new for us. We’re creating a tech-driven business to empower and equip our people to be outstanding in delivery, no matter where they work – through inspiring collaboration spaces and new technologies. In your role, you’ll work flexibly across your location region – at engagement sites, our offices and home. Some travel is likely for audit work and because the work is seasonal, you can expect a greater workload at the busiest times of the year.
Join us and be empowered to grow in your own way and make your mark.
At KPMG, everyone brings a unique perspective, and we want to ensure that you have the best opportunity to demonstrate your potential. We’ve designed our application process to assess everyone’s potential in the context of their educational and personal circumstances to ensure that you have the skills to succeed at KPMG.
You’ll generally be expected to demonstrate the following (*or equivalents). However, if you do not meet all the below, and are a few grades or points short, then we would still encourage you to apply, as you will be given the option to provide additional information that enables us to assess your application and potential in the context of your socio-economic background and/or any extenuating circumstances. You can find out more here.
- 5 GCSEs* at A* – C or at 4 – 9 (inc. English Language and Maths at Grade B or 5), or for Scotland 5 National 5 qualifications at Grades A – C (inc. English Language and Maths at Grade B or equivalent)
- 120 UCAS points* from your ‘top’ 3 grades, excluding General Studies under the 2017 tariff point system at A Level (300 UCAS points pre-2017) or at Higher/Advanced Higher Level for Scotland.
Throughout the recruitment process we will be looking to learn more about your strengths.
To be successful on this programme, you will be required to demonstrate the strengths that we look for in our apprentices at KPMG.
Learn more about what we look for and how to apply here.
The training and development of our people is critical to the future success of our business. We want all of our Apprentices to embrace a growth mindset of learning every day, which is why we have created a rich curriculum and learning community to help trainees build their skills and fulfil their potential. This ranges from an immersive 5-day induction experience, formal training courses, leadership knowledge bites, learning journals, online courses and networking events – all aligned to our life-long learning strategy and part of our overall student package.
In addition, as part of your KPMG Audit Data & Analytics Apprenticeship you will complete the Digital and Technology Solutions professional Level 6 qualification.
The Digital and Technology Solutions qualification is delivered via masterclasses, workshops and 1:1 coaching providing support at every stage of your qualification and apprenticeship. You will continuously apply what you are learning in training to your workplace experience through your apprenticeship skills and behaviours and off-the-job (OTJ) training. In addition, we will make sure you have the base line professional services knowledge you need to thrive by also having you complete some AAT modules prior to commencing your studies in the Level 6 D&A.
You will have both wrap around support which consists of dedicated professional coaches, online portal content and additional study sessions, which means there is a form of support for your every need.
Please note, if you have started or obtained a degree (or equivalent) in Data Analytics or similar field to the professional qualifications provided on the programme, please contact the Student Recruitment team to check your eligibility before making an application.
Please visit our Applying to KPMG page to discover more about our application process.
Visit our International Students page to find out more about visas and requirements.
For anything else, please refer to our FAQ section.
