Analyst - Risk & Resilience

McKinsey & Company
parental leave, paid time off
United States, New York, New York
Jan 15, 2025
Consulting Analyst - Risk & Resilience Job ID: 94186 Are you driven by the opportunity to tackle complex challenges and work alongside top leaders? Do you want to be part of a team that delivers outcomes that others simply can't? If so, you've come to the right place. Who You'll Work With You'll work at client offices, our Boston or New York City office focusing on risk analytics as a member of our data analytics team, part of McKinsey's global Risk & Resilience practice. Our global Risk & Resilience practice helps clients understand, prepare for, and manage risks to ensure institutional resilience in an ever-changing world. Our team is a global leader in risk analytics and model governance, working with banks, asset managers, insurance firms, and other leading infrastructure players around the world. We help our clients create sustainable modelling and analytics platforms to support their businesses in a data-driven world. From core regulatory capital and risk models to business decision analytics and model risk management, we create value by improving performance across the model lifecycle. Our model development, model validation and model risk advisory work spans multiple risk functions, markets, operating challenges and modeling techniques. When delivering a project, we strive to advance our client's understanding of both well-established and emerging risk management techniques. Our experienced team incorporates risk specialists, quantitative experts and business professionals empowering us to offer our clients a unique variety of skills in risk management, business, and regulatory compliance. While we tailor every service to suit each client's need, our identity is unwavering with bedrock values including excellence, teamwork, integrity and innovation. Our work requires rigorous understanding of underlying modeling techniques as well as of the business context in which those models are being used. We are therefore looking for candidates who can establish connections between sophisticated modeling techniques and strategic decision-making processes. Your impact within our firm You will work to construct statistical models and complete targeted quantitative analyses across different techniques (e.g., regressions, machine learning, simulations) that allow companies to make better analytically based decisions across the spectrum of risk management. Your responsibilities will include developing and validating models including credit (e.g., underwriting, portfolio management), stress-testing, cash-flow modeling, and hedging. You'll work on client projects as an integral part of engagement teams and you will contribute to internal knowledge development initiatives. You'll disaggregate and structure complex, often ambiguous, business problems and evaluate different analytical approaches to develop potential solutions. You will apply advanced analytical and quantitative tools, statistical modeling techniques and data mining procedures to derive business insights and solve complex business problems. Further, you will develop components of statistical models, writing and developing scripts (e.g., SAS scripts) to improve risk management decision making (e.g., underwriting models). You will contribute to team problem solving through the findings and insights from your analysis and help facilitate data integration and management between clients and McKinsey. Ultimately, you will contribute to the development of knowledge for the analytics group at large. Your qualifications and skills Master's degree in a quantitative field such as mathematics, statistics, analytics, computational finance, computer science, economics, financial engineering, physics, or other relevant field 1+ years' of hands-on experience in quantitative modeling using advanced analytics tools (e.g. Python, R) to solve real world problems Demonstrated understanding of financial mathematics including stochastic calculus and probability theory, as well as derivative pricing models and other numerical techniques across a variety of asset classes (e.g., equities, rates, credit, FX and commodities) with practical experience in using MATLAB/C++/R/VBA Experience programming (beyond simple scripts) in a modern scientific language (e.g., Python, Matlab, R) and experience with TensorFlow, Spark, Java, C#, C++, or C; knowledge of SQL and SAS is a plus Knowledge of VaR (historic, parametric, MonteCarlo), EOD or intra-day risk & valuation, as well as stress-testing and scenario analysis is a plus Critical thinker who can develop an opinion and support it with persuasive arguments based on available evidence Ability to execute an analytics process from problem specification through to solution in your area of expertise Ability to work collaboratively in a team environment and effectively with people at all levels in an organization; can build constructive relationships both with colleagues and clients Adaptable to rapidly changing timelines and objectives; able to work under pressure with tight deadlines while maintaining quality of outputs Exceptional verbal and written communication skills, especially around translating technical knowledge into accessible forms for non-technical project teams, leadership, and clients Willingness to travel Please review the additional requirements regarding essential job functions of McKinsey colleagues. Apply Now Apply Later FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law. Certain US jurisdictions require McKinsey & Company to include a reasonable estimate of the salary for this role. For new joiners for this role in the United States, including all office locations where the job may be performed, a reasonable estimated range is $112,000 - $112,000 USD -to help you understand what you can expect. This reflects our best estimate of the lowest to highest [salary/hourly wages] for this role at the time of this posting, ensuring you have a clear picture right from the start, though it's important to remember that actual salaries may vary. Factors like your office location, your unique blend of experience and skills, start date and our current organizational needs all play a part in determining the final figure. Certain roles are also eligible for bonuses, subject to McKinsey's discretion and based on factors such as individual and/or organizational performance. Additionally, we provide a comprehensive benefits package that reflects our commitment to the wellness of our colleagues and their families. This includes medical, mental health, dental and vision coverage, telemedicine services, life, accident and disability insurance, parental leave and family planning benefits, caregiving resources, a generous retirement contributions program, financial guidance, and paid time off. FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites. Job Skill Group - CSS Pre-Associate Job Skill Code - AF - Analytics Fellow Function - Risk & Resilience Industry - Financial Services Post to LinkedIn - #LI-DNI Posted to LinkedIn Date - LinkedIn Posting City - LinkedIn Posting State/Province - LinkedIn Posting Country - LinkedIn Job Title - Analyst - Risk & Resilience LinkedIn Function - LinkedIn Industry - LinkedIn Seniority Level -