The fastest growing Big Four professional services firm in the U.S., KPMG is known for being a great place to work and build a career. We provide audit, tax and advisory services for organizations in today’s most important industries. Our growth is driven by delivering real results for our clients. It’s also enabled by our culture, which encourages individual development, embraces an inclusive environment, rewards innovative excellence and supports our communities. With qualities like those, it’s no wonder we’re consistently ranked among the best companies to work for by Fortune Magazine, Consulting Magazine, Working Mother Magazine, Diversity Inc. and others. If you’re as passionate about your future as we are, join our team.

KPMG is currently seeking a Manager, Data Scientist - Optimization, to join our Advanced Data and Analytics Organization.

Responsibilities:

• 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

Qualifications:

• Master's 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; PhD with minimum of one year of experience is preferred
• 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. Java, Python, Ruby) as well as the ability to implement, maintain, debug and test; experience in commercial optimization solvers (e.g. CPLEX, Gurobi, Xpress) preferred
• Experience in software development, ideally as part of a team using version control systems such as Git or SVN
• 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 20-50% with the possibility of up to 80%

KPMG LLP (the U.S. member firm of KPMG International) offers a comprehensive compensation and benefits package. KPMG is an equal opportunity employer. All qualified applicants are considered for employment without regard to race, color, creed, religion, age, sex/gender, national origin, ancestry, citizenship status, marital status, sexual orientation, gender identity or expression, disability, physical or mental handicap unrelated to ability, pregnancy, veteran status, unfavorable discharge from military service, genetic information, or other legally protected status. KPMG maintains a drug-free workplace. KPMG will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable local, state or federal law (including San Francisco Ordinance number 131192). No phone calls or agencies please.