You&039;ll be an important part of our high-energy, unique, fast-paced, and innovative culture that delivers with the agility of a tech startup and the backing of a leading global consulting firm. In this particular role, you&039;ll work specifically in the AI Analytics & Engineering Community within KPMG, on a wide range of projects. From applied AI to optimization to big data platform engineering, your analytical and technical skills will drive real impact in the business world. At KPMG, our commitment to your career development helps to set us apart as an employer. We want to enhance your potential, both for yourself and as a contributor to our firm. That&039;s why we provide every opportunity to expand your skills, knowledge and experiences through formal education and training programs, leadership development opportunities, and, as well as informal one-on-one coaching and mentoring from your KPMG colleagues
Key Roles and Responsibilities:
• Translate advanced business analytics problems into technical approaches that yield actionable recommendations, in diverse domains. Communicate technical details of solution, including mathematical formulations, alternatives, and impact on modeling approach to business stakeholders across industries, especially financial service sector.
• Lead and build up multi-disciplinary and cross-functional teams to rapidly iterate models and results to refine and validate approach; Lead team in a fast-paced and dynamic environment with both virtual and face-to-face interactions; Utilize structured approaches to solving problems, managing risks, and multiple responsibilities using structured approaches for operational excellence; Communicate results to executive level audiences.
• Work internally within KPMG&039;s other areas within Advisory, Audit, Tax to advance the client understanding of Data Science, Artificial Intelligence, and Advanced Analytics.
• Plan engagement objectives, key deliverables, and deliver on engagement milestones by following analytics processes; Work with clients to discover, retrieve, prepare, and process a variety of data sources (social media, news, internal/external documents, emails, financial, and operational).
• Leverage deep technical knowledge to build, review, and quality control code to prepare, extract, and enrich data sources, working with the business to understand available resources and constraints around data. Lead team in exploratory data analysis, generating and testing working hypotheses, and uncovering interesting trends and relationships. Provide expert oversight for teams building machine learning algorithms and data science solutions.