KPMG Senior Associate, Operation Research Data Scientist in Knoxville, Tennessee
Business Title: Senior Associate, Operation Research Data Scientist
Requisition Number: 73226 - 80
Area of Interest: Digital Lighthouse
Innovate. Collaborate. Build. Create. Solve. The KPMG Digital Lighthouse is KPMG's award-winning Analytics & AI Center of Excellence recognized by clients and leading analyst firms in the US and globally. The KPMG Lighthouse is a curation of specialized technical capabilities and domain experts working across the digital landscape: applied data science, AI, data engineering and insights, software engineering, automation, and big data. Here, you'll work with a diverse team of professionals to explore and build solutions for clients in a multiplatform environment.
You'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'll work specifically in the AI Analytics & Engineering Community within the Digital Lighthouse, 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'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.
KPMG is currently seeking a Senior Associate, Operations Research Data Scientist to join our KPMG Lighthouse (https://home.kpmg.com/us/en/home/insights/2015/01/data-and-analytics.html?location=us) - Center of Excellence for Advanced Analytics.
Apply various optimization techniques to generate solutions to large-scale optimization problems for KPMG clients, such as resource planning, scheduling, facility location, portfolio optimization, and pricing/revenue optimization. Techniques include but are not limited to linear/mixed-integer programming with commercial (e.g. CPLEX) as well as open-source solvers (e.g. CBC), dynamic programming, heuristics, metaheuristics, and more
Develop and employ simulation models (Discrete Event, Agent-Based, and System Dynamics modeling) by using simulation software AnyLogic (Preferred), NetLogo, Simulink and/or AREN
Process structured, unstructured and semi-structured data and apply data cleaning, data imputation and feature engineering methods prior to developing models
Develop predictive models using Machine Learning (e.g. classification, clustering, regression, dimensionality reduction methods), Natural Language Processing (OCR, information extraction), and statistical analysis methods such as time-series analysis, 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 Python, R, Julia, C++, Tableau, and more
Bachelor's Degree and two years of relevant work experience OR an Advanced degree (Master's or PhD) in Operations Research, Computer Science, Applied Mathematics, Industrial Engineering, or related field from an accredited college or university
Professional knowledge of advanced analytical concepts, particularly ModSim (Modeling & Simulation), Optimization and Machine Learning
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 programming languages (e.g. Python, R, C++, Julia), data analysis packages (e.g.scikit-learn, pyomo) 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
Professional experience with high proficiency in the use of Microsoft Office programs (Word, PowerPoint, Excel)
Ability to travel when necessary; 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, age, 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 ( https://assets.kpmg.com/content/dam/kpmg/us/pdf/2018/09/eeo.pdf) contains further information regarding the firm's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.
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