Associate Director, Data & Analytics – Africa at KPMG

Job Description

KPMG is a professional service company, being one of the Big Four auditors, along with Deloitte, EY and PwC. Seated in Amsterdam, the Netherlands, KPMG employs , people and has three lines of services: audit, tax, and advisory.

Position Summary

At KPMG, you’ll find a world of opportunity, where our people give clients and communities the insights, they need to build a sustainable future. We seek an experienced individual with a strong track record in building AI, ML and Deep Learning algorithms to help our clients harness the power of data. This is a Full Time, Hybrid Pan-African role, with responsibility for leading a team across the continent, and the resource will be based in either Johannesburg, Nairobi, or Lagos.

Role and Responsibilities

Strategy

 Provide technical data & analytics support to the Africa digital transformation team.  Leverage regional alliances with technology partners (e.g. Microsoft, Oracle, IBM, AWS, Google, etc) to drive proactive leads generation, joint pitch, pipeline management and conversions as they relate to data analytics.  Work with relevant functional areas and service lines across the Firm to deliver on client engagement and sales initiatives.  Leverage local and global KPMG artefacts, SMEs, and other network assets to advance the firm’s data & analytics agenda.  Manage, coach and grow the ML engineering and data science team.  Embed data & AI in everything we do – meaning that you will also be responsible for exploring and improving collaboration with different competences within KPMG.

Client Impact

 Drive business growth of the Data & Analytics business across Africa through expansion of ML engineering pipeline and wins at leading clients.  Oversee data management, warehousing, integration, and migration; business intelligence; analytics; and delivery across advisory and technical projects.  Lead the development and implementation of data and advanced analytics strategies for clients across Africa.  Develop ML and Deep Learning algorithms that help clients improve their predictive capabilities significantly.  Design, develop, maintain and improve machine learning algorithms for the clients’ products.  Help clients to employ machine learning principles in making business decisions.  Collaborate with the D & A team to build data pipelines, implement and train models based on results of experiments.  Interact with business leaders and functional experts to understand current and future business challenges and needs and help with solutioning.  Provide subject matter expertise on data-related topics as well as consultative guidance for data management and governance.  Develop data models that improve processes and add strategic value to the client’s business.  Stay up to date with industry trends and emerging technologies in data and analytics to ensure we provide clients with the latest and most effective solutions.  Work closely with clients to understand business needs and develop tailored solutions.  Strengthen KPMG’s share of mind in the D & A space through impactful thought leadership.

Finance

 Deliver on targets and goals (including sales goals).  Provide annual budget input for the area of responsibility for approval and integration into service line/ growth area budget.  Manage the annual budget, including costs for designated area.

Qualifications, Experience and Skills

The ideal candidate has:

 Bachelor’s or Master’s degree in a relevant field such as computer science, statistics, mathematics, or related fields.  A minimum of 5 O’ Level credits (including English and Mathematics).  Minimum of 10 years’ experience in AI and ML engineering with a proven track record of delivering successful projects.  Deep knowledge of programming languages and frameworks such as Python, Java, C++, R, and SQL.  Deep hands-on experience with modern Data & AI Platforms such as Azure, AWS or GCP.  Practical experience with tools like Git/Github for version control, Jenkins for continuous integration, and Docker for containerization.  Deep understanding of data and analytics technologies, including data warehousing, data integration and data visualization.  Good understanding of statistics, probability theory, and computer science fundamentals like algorithms and data structures.  Pre-sales experience with OEMs or consulting experience will be an added advantage.  Being a self-starter and able to work independently including across multiple priorities and complex matrixed roles and responsibilities.  Confident, tactful and able to effectively influence others and deal effectively with senior leaders.  Strong communicator, including listening skills with an ability to translate insights across business and technology teams and to develop and present new ideas and conceptualize new approaches and solutions.  Strong team and work ethic, comfortable with ambiguity, change and challenge.  Interested in the bigger picture and able to think broader than own capabilities.  Ability to connect with the right complimentary people in KPMG to tackle new and complex business problems with a data flavour.  Enthusiastic, driven and proactive