* 5+ years of professional experience in machine learning, mathematical modeling, statistical modeling, optimization or data mining involving large data sets
* Ideally have professional experience in a financial services related industry (e.g., banking and securities, asset management, insurance)
* At least 2 years of experience with current data visualization applications and tools
* Master's or PhD degree in a quantitative field such as statistics, math, applied mathematics, financial mathematics, etc.
* In depth understanding of risk measurement frameworks, including the ability to identify and communicate risk concentrations and key drivers of risk and capital via presentations or reports
* Working knowledge of Generally Accepted Accounting Principles (GAAP), Basel III, Dodd-Frank Act Stress Testing, and bank accounting/regulatory reporting requirements
* CFA, PRM, or FRM designation or candidate
* Required experience in R, Python and/or Tensorflow
* Applied Machine Learning modeling expertise is required
* Background in Deep Learning (CNN, LSTM), Natural Language Processing (Word2Vec), and Anomaly Detection is highly preferred
* Desired experience in Java, PHP, J#.Net environment, Perl, Mathematica, MATLAB, Hadoop, Spark, SAS, STATA, SPSS, RapidMinder, S-plus, ARC-GIS, Weka, NetLogo, MASON, RePast
* Desired experience using other programming and data manipulation languages (SQL, Hive, Pig, C/C++)
* Solid MS Office skills - Excel (including macros and VBA) and Access (or SQL), storyboarding and PowerPoint at high proficiency preferred
* Knowledge of any one visualization tool such as Tableau, Spotfire, PowerView, QlikView, D3.js or equivalent
* Experience in developing advanced models such as multivariate regression, neural networks, support vector machines, Random Forest, Bayesian Analysis, decision trees, ANOVA, etc.
* Well-honed analytical problem-solving ability coupled with business acumen to structure problems, deliver solutions and communicate insights
* Strong quantitative and conceptual thinking skills, with attention to detail and accuracy
* Entrepreneurial, driven spirit; strong ownership mindset with a focus on delivering high-quality end products
* Energetic, self-starter who thrives in a collaborative, fast-paced environment
* Polished interpersonal and communication style with the ability to effectively communicate, persuade and clearly explain complex technical insights to a wide variety of audiences
* Ability to travel up to 50-75%
Who You'll Work With
You'll join our New York office as part of our Risk practice, focused on machine learning.
This global practice supports clients in many different industries facing challenges of developing and implementing tailored concepts for risk recognition, measurement, and control. Facing extreme volatility in financial and commodity markets, more and more of our clients are realizing that effective, risk-informed strategy can offer a major source of competitive advantage. We take a truly global, cross-sector, cross-functional view of risk issues, combining McKinsey's deep industry insight and strategic skills with a structured risk-management approach, proven methodologies focused on true transformation, analytical tools, and practical implementation.
When you join McKinsey as an Associate, you are joining a firm that will challenge you and invest in your professional development. In this role you will work on the best teams to help the best organizations in the world - in private, public, and social sectors - solve their most difficult problems. You will also work with many experts, from data scientists and researchers to software and app designers.
What You'll Do
You will work closely with client teams to assess business opportunities, identify and prioritize gaps in business performance and develop and implement solutions that leverage data to achieve sustainable success.
As an associate, you'll apply your deep technical knowledge of machine learning to serve as a strategic consultant to clients, work in a demanding but highly collegial and collaborative environment. You'll have the opportunity to develop and maintain consultative relationships with key business stakeholders, proactively identifying and addressing their needs.
You'll collect, clean and analyze quantitative data to develop critical insights and pragmatic data solutions for our clients' issues and you'll source, scrub, and join relevant public, commercial, and proprietary data sources. You'll have the chance to integrate and mine large data sets, connecting data from disparate sources to identify insights and patterns using traditional as well as predictive and prescriptive analytics and you'll analyze and visualize financial and operational data through the development of interactive descriptive analytics dashboards.
Additionally, you'll design and create advanced predictive models such as support vector machines, neural networks, decision trees, etc., allowing our clients to make more informed business decisions. You'll be expected to produce and deliver analytic insights, findings and recommendations in succinct, compelling presentations to a team of colleagues and clients and you'll also provide mentorship and training to junior colleagues while maintaining progress on all initiatives under minimal direct supervision.
Associates receive exceptional training as well as frequent coaching and mentoring from colleagues on their teams. This support includes a partner from your local office or practice assigned to you to help guide your career as well as up to five weeks of formal training in your first two years as an associate. Additionally, you'll receive guidance and support from your local office or practice in the selection of client projects, helping you to develop your skills and build your network.
McKinsey & Company is an equal opportunity employer.
McKinsey and Company is a management consulting firm serving commercial, government, and not-for-profit organizations.