Senior Data Scientist - Risk Management
QUALIFICATIONSMaster's degree or PhD in a quantitative discipline such as statistics, mathematics, econometrics, economics, operations research, computer scienceAt least 4 years of experience in a commercial environmentSignificant experience working with large data sets and using quantitative analysis/modeling to drive business resultsStrong experience in working in quantitative teams focused on financial or non-financial risk, with a high degree of independence and responsibilityStrong experience in, or a desire to learn about risk management, including operational risk, credit risk, anti-money-laundering, fraud detectionProven experience in applying machine learning algorithms such as Neural Networks, Support Vector Machines, CART, etc.Deep experience with analytical software (e.g. R) and solid working knowledge of scripting languages (e.g., Python). Experience with databases (SQL or NoSQL) would be beneficial Some experience in leading projects and overseeing junior colleaguesExceptional communication skills, especially around translating technical knowledge into forms that can be digested by leadership and non-technical project teamsTeam player, with a professional and service-oriented attitude Ability to work effectively and collaboratively with people at all levels in an organizationWHO YOU'LL WORK WITHMcKinsey UK's Risk Management practice, part of the Risk Advanced Analytics (RAA) group, and based in London is looking for Analytics Specialists to join the team. Our global Risk Management practice supports clients in many different industries facing challenges of developing and implementing tailored concepts for risk recognition, measurement, and control.WHAT YOU'LL DOYou will be at the centre of the Risk Analytics group's analytical engine, implementing machine-learning techniques for our client projects in the area of risk management. Additionally, you will be responsible for team oversight as well as some project management. In doing so, you will balance independent modeling and analytical work with oversight of firm teammates, including fellows and analysts.Building upon your ideas and experience, you will apply machine learning algorithms to risk modeling to gain new insights and translate them into distinct client contributions. You will be fully integrated into client service teams. This includes gathering and analysing information, formulating and testing hypotheses, and developing and communicating recommendations. You will also present results to clients and implement recommendations in collaboration with client team members.You will use a broad range of internal and external data sources in your work. You will contribute to knowledge development by helping define and expand distinctive risk-based methodologies to support top management-level strategic decisions.