Analyst, Strategic Value Advisory

Kroll•New York, NY

18h•$60,000 - $90,000

About The Position

Kroll’s Strategic Value Advisory practice provides quantitative consulting services that solve business problems through the analysis of risk and value. We provide our clients with quantitative and financial modeling and risk analyses to support mergers and acquisitions, intellectual property (IP) licensing, capital investment decisions, financial reporting and tax valuations, and complex commercial litigation including IP litigation and contract disputes. We focus on hard-to-value items like IP portfolios, early-stage companies, and contingent assets and liabilities. We also provide analyses of product development investments and business growth strategies. Our Analysts receive world-class training, outstanding benefits, strong career progression, competitive salaries and relocation assistance when applicable. We embrace diverse backgrounds and global perspectives, and we cultivate diversity by respecting, including, and valuing one another. As part of One team, One Kroll, you’ll contribute to a supportive and collaborative work environment that empowers you to excel. In a world of disruption and increasingly complex business challenges, our professionals bring truth into focus with the Kroll Lens. Our sharp analytical skills, paired with the latest technology, allow us to give our clients clarity—not just answers—in all areas of business.

Requirements

Currently pursuing or recently completed a bachelor’s, master’s, or doctoral degree in mathematics, statistics, quantitative economics, operations research, management science, physics, or a closely related field from an accredited college or university
Available to start between August 2026 and January 2027
Current cumulative GPA of at least 3.5
Enjoyment of applying quantitative techniques to challenging, real-world problems
Solid understanding of mathematical concepts, probability, and statistics
Strong analytical, critical thinking and problem-solving skills
Ability to evaluate alternatives and exercise sound judgment when applying quantitative methods to new or complex problems
Intellectual curiosity and desire to work on many projects across a wide variety of industries and subject areas
Excellent verbal and written communication skills, including the ability to explain complex quantitative concepts clearly
Ability to manage multiple assignments, priorities, and deadlines in a rapidly changing, collaborative environment
Demonstrated commitment to focus on quality and strong attention to detail
Willingness to take initiative and personal responsibility, learn new concepts, work independently, and master new methods quickly
Experience working effectively with diverse teams from different professional, academic, and personal backgrounds

Nice To Haves

Programming or statistical modeling experience using VBA, MATLAB, R, SAS, STATA, Python, or a comparable language and/or statistical package is preferred

Responsibilities

Collaborating with colleagues to devise innovative solutions to client problems
Working closely with clients and engagement teams to develop financial, statistical, and decision models
Evaluating alternative modeling methodologies, assumptions, and data source and recommending appropriate analytical approaches
Programming, testing, and running financial models and “what if” analyses
Conducting expert interviews and performing industry research
Analyzing data using techniques such as statistics, econometrics, probabilistic modeling, real options models, Monte Carlo simulation, and other quantitative modeling and analytics techniques
Interpreting analytical results and translating them into clear findings relevant to client decisions
Writing reports, making presentations, and assisting in group facilitation
Planning and executing assigned analytical workstreams under general supervision while managing multiple deadlines and changing priorities
Assisting in client proposals and developing new business
Participating in internal strategic initiatives related to improving methodologies and increasing operational efficiency