Lead Specialist, Deal Advisory & Strategy Analytics - TMT - #7932946
Historically, the travel requirement for this position has ranged from 80-100%. The safety and well-being of our people continues to be the top priority, and our decisions around travel are informed by government COVID-19 response directives, recommendations from leading health authorities, and guidance from a number of infectious disease experts. For now, all KPMG business travel, international and domestic, is currently restricted to client-essential sales/delivery activity only. At some point in the future and with the safety of people as the critical factor, the travel requirement will likely increase, possibly to previous levels, but KPMG is committed to balancing client requirements with new delivery capabilities.
The KPMG Advisory practice is currently our fastest growing practice. We are seeing tremendous client demand, and looking forward we don't anticipate that slowing down. In this ever-changing market environment, our professionals must be adaptable and thrive in a collaborative, team-driven culture. At KPMG, our people are our number one priority. With a wealth of learning and career development opportunities, a world-class training facility and leading market tools, we make sure our people continue to grow both professionally and personally. If you're looking for a firm with a strong team connection where you can be your whole self, have an impact, advance your skills, deepen your experiences, and have the flexibility and access to constantly find new areas of inspiration and expand your capabilities, then consider a career in Advisory.
KPMG is currently seeking a Lead Specialist in Financial Due Diligence for our Deal Advisory practice.
Analyze data using statistical techniques such as regression, machine learning clustering, A/B testing, and time series modeling/forecasting
Balance statistical rigor and thoroughness with cost and speed based on the client's budget and time frame
Perform explanatory data analysis, generate and test working hypothesis, prepare and analyze historical data and identify patterns
Generate repeatable data and analytic processes using tools such as R, Python, Hive, Alteryx, Tableau, and SQL Server
Work with cross-functional KPMG team members to develop and present findings
Own or participate in every component of a client deliverable, from identifying client needs to producing the final presentation and reports
Master's degree in Computer Science, Statistics, Mathematics, Engineering, Econometrics, or related fields, with three years of relevant experience and strong knowledge in at least one of the following fields: statistics, data mining, machine learning, operations research, or econometrics; PhD is preferred
Experience with the ETL process and familiarity with SQL and HiveQL; Spark experience a plus
Ability to learn new data science and analytic tools quickly according to the needs of our team and our clients
Strong communication skills with the ability to explain technical concepts and analytics-driven findings to business people potentially including C-level executives, and to explain business processes, concepts, challenges, and issues to technical resources
No travel will be required
Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future
KPMG LLP (the U.S. member firm of KPMG International) offers a comprehensive compensation and benefits package. KPMG is an affirmative action-equal opportunity employer. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other category protected by applicable federal, state or local laws. The attached link contains further information regarding the firm's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.