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 Manager, Data & Analytic Modeler, Optimization Consultant for our Consulting practice.
Apply various discrete optimization techniques to generate solutions to large-scale optimization problems for KPMG clients, such as resource planning, scheduling, facility location, and network optimization; techniques may include integer programming including commercial solvers, event simulation, dynamic programming, local heuristics, metaheuristics, and more
- Develop predictive models using machine learning, natural language, and statistical analysis methods such as classification, time-series analysis, regression, statistical inference, and validation tools; perform exploratory data analyses, generate and test working hypotheses, prepare and analyze historical data, and identify patterns
- Work directly with KPMG clients and stakeholders to present and explain the key techniques and major results generated using non-technical language; understand client feedback and be able to accommodate it into model through programming
- Come up with innovative, repeatable, business use cases for real world optimization techniques, and quickly develop prototypes to test these use cases
- Utilize a diverse array of technologies and tools as needed, to deliver insights, such as R, SAS, Python, Tableau, and more
- PhD degree in Operations Research, Computer Science, Applied Mathematics, Industrial Engineering, or related field from an accredited college or university with five years of relevant experience;
- Experience utilizing a strong mathematical background with advanced knowledge in one or more of the following fields: discrete optimization, integer programming (including commercial optimization solvers), discrete-event simulation, dynamic programming, local search heuristics, genetic algorithms, or other metaheuristics
- Proficiency in data analysis packages (e.g. R, SAS, Matlab), programming languages (e.g. C++, Python, Ruby) as well as the ability to implement, maintain, debug and test; experience in commercial optimization solvers (e.g. CPLEX, Gurobi, Xpress)
- Experience in software development using version control (Git), unit testing, Jira, and Confluence.
- Ability to work with team members and clients to assess needs, provide assistance, and resolve problems, using excellent problem-solving skills, verbal/written communication, and the ability to present and explain technical concepts to business audiences
- Ability to travel up to 80% of the time; 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.