Short DescriptionMcKinsey is looking for Associate-Machine Learning who has good experience in developing advanced models such as multivariate regression, neural networks, support vector machines, Random Forest, Bayesian Analysis, decision trees, ANOVA, etc.
- 5+ years of professional experience in machine learning, mathematical modeling, statistical modeling, optimization or data mining involving large data sets.
- At least 2 years of experience with current data visualization applications and tools.
- 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.
- Applied Machine Learning modeling expertise is required.
- 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.
- Solid MS Office skills - Excel (including macros and VBA) and Access (or SQL), storyboarding and PowerPoint at high proficiency preferred.
- Experience in developing advanced models such as multivariate regression, neural networks, support vector machines, Random Forest, Bayesian Analysis, decision trees, ANOVA, etc.
- Strong quantitative and conceptual thinking skills, with attention to detail and accuracy.
- Polished interpersonal and communication style with the ability to effectively communicate, persuade and clearly explain complex technical insights to a wide variety of audiences.
- Entrepreneurial, driven spirit; strong ownership mindset with a focus on delivering high-quality end products.
- Well-honed analytical problem-solving ability coupled with business acumen to structure problems, deliver solutions and communicate insights.
- Knowledge of any one visualization tool such as Tableau, Spotfire, PowerView, QlikView, D3.js or equivalent.
- Desired experience using other programming and data manipulation languages (SQL, Hive, Pig, C/C++).
- Required experience in R, Python and/or Tensorflow.
- Master's or PhD degree in a quantitative field such as statistics, math, applied mathematics, financial mathematics, etc.