Expert - Risk Analytics

Qualifications

  • Advanced degree (Masters or PhD) in a quantitative discipline such as computer science, mathematics, statistics, physics, or engineering
  • 10+ years of experience leading the end-to-end development and deployment of leading edge quantitative risk management solutions ideally in the financial services related industry (e.g., banking and securities, asset management, insurance)
  • Experience managing analytic resources (e.g., data, analytics, visualization) to create measurable business impact
  • Experience working in/with enterprise class data environments to access, manipulate and analyze large data sets
  • Strong consulting skills; previous experience in a client service-oriented role
  • Distinctive expertise and leadership experience in at least one of the following: operations risk, trading risk, fraud detection, or credit risk
  • In-depth understanding of the application of modern machine learning / AI, including natural language processing, deep learning, anomaly detection, and graph-based models to risk management
  • Solid expertise using core statistical learning algorithms including linear models, segmentation, dimension reduction, ensemble models, SVMs, and kernel methods to analyze large structured and unstructured datasets
  • Very strong experience programming (beyond simple scripts) in a modern scientific language (e.g., Python, Matlab, R) and some experience with Java, C#, C++, or C. Knowledge of SQL and SAS would be a plus
  • Exceptional communication skills, demonstrating an ability to engage with and persuasively present to a wide variety of audiences (e.g., with and without technical background, senior and mid-level clients)
  • Strong project management skills; flexibility and ability to manage multiple assignments in a dynamic, complex and fast-paced environment
  • Proven comfort and an intellectual curiosity for working with very large sets of data integration
  • Demonstrated ability to lead high functioning teams, mentor more junior colleagues, and rapidly build capabilities
  • Highly ambitious – seeks accountability in a challenging business environment and thrives on success through innovative problem solving
  • Willing to travel 50-75%

Who You'll Work WithYou will be based out of our New York office, a Risk hub, and will work with client teams to provide technical leadership and own significant parts of advanced model development. Our Risk practice is global so although you will primarily be serving clients in the Americas, you will also support clients in other geographies and across many different industries that are facing challenges of developing and implementing tailored concepts for risk identification, measurement and control.

What You'll Do

You will work with client teams to provide technical leadership to solve our client's Risk Management related business problems.

You will support teams in the application of state-of-the-art advanced analytic and quantitative tools to derive insights and improve risk management decision making for clients. You will oversee end-to-end delivery of projects, working with team and practice leadership to ensure delivery of an analytics component (e.g., engage in problem solving; plan and manage execution) and proactively shaping the innovation / capability building agenda. You will help build capabilities with clients and project teams by codifying your knowledge, mentoring colleagues, and helping to drive internal knowledge development efforts.

Your role will be divided into three broad sets of responsibilities: Risk Advanced Analytics, Client Service Support and Knowledge Transfer and Practice Development. We expect that with your 10+ years of experience, that you will offer distinctive problem-solving leadership on a range of topics to break down complex business problems into tangible components that can be solved using insights derived from analytic techniques. You will apply advanced analytic and quantitative tools, statistical modeling techniques, and data mining procedures and tools to develop solutions, set up data sets and databases with the data received from clients and other 3rd parties and act as the 'go-to' person for all analytical questions for both clients and internal teams; be the day-to-day client contact on analytically intensive engagements. You will own the development of statistical models writing code and developing scripts (e.g., Python scripts) to improve Risk management decision making (e.g., underwriting models) and lead the integration of different solution components developed by other team members including junior colleagues. You will translate business requirements into technical needs and appropriately scope analysis and end deliverables as well as translate results from analysis and models into tangible business insights. You will provide thought leadership to ad-hoc Risk Analytics-related requests from other client engagement teams.

All of this is done in a way to create value for clients by understanding their needs and translating them into the required analytic work products by contributing to team problem solving through findings and insights from your analysis to help facilitate data integration and management between clients and McKinsey.


Meet Some of McKinsey's Employees

Danielle B.

Partner

Danielle is one of the leaders of McKinsey’s business with retail and consumer clients. She oversees client projects and helps her teams and her clients utilize McKinsey’s resources.

Fope F.

Senior Associate

Fope helps lead a small team that works for McKinsey clients, helping them address business challenges and strategic questions. Though based in the NYC office, she travels frequently so she can be in-person with her clients.


Back to top