Role/Responsibilities The VP Data Science is a key member of the Analytic and Technology Solutions (ATS) group in MIS. ATS is responsible for developing the quantitative models and analytical tools used in the rating process and across the rating agency, as well as MIS technology innovation activities, including advanced capabilities in machine learning and artificial intelligence. The VP Data Science will be responsible for helping manage application of the latest techniques in Machine Learning and Distributed Computing to drive business value. A successful candidate will not only be technically competent, but will be able to work collaboratively with business stakeholders to increase analytical efficiency, drive new business insights, and develop new products. The role also includes advocating for operational and process changes to move towards a more data driven organizational paradigm.
The duties of the VP Data Science include:
Manage development and deployment of Machine Learning / Statistical Learning models for predictive analytics
Provider leadership in staying up to date with the developments in relevant technologies and market trends (including statistical and machine learning methods) to identify enhancements
Work collaboratively with relevant stakeholders and partners to develop and release cutting-edge tools that address business needs
Evaluate and apply sound software and architectural development practices in development and deployment of models as software products.
Manage usage of cloud and distributed computing platforms for model development and deployment
Communication of results to business stakeholders and decision makers
Speak internally and/ or at external events as required
Analytic and Technology Solutions Group
Master's Degree in Computer Science, Statistics, Applied Math, specialized Machine Learning program, or related field
12+ years practical experience in Machine Learning or statistics and/or distributed computing
Proven track record of successfully building machine learning models and other applications
Knowledge of Machine Learning techniques include Neural Networks, Tree-based Models, Linear models
Industry knowledge of Fixed Income in Public Finance and/or Structured Finance is highly preferred
Experience with one or more of the following programming languages is highly preferred: Python, R, Scala, and SQL
Experience with one or more of the following Machine Learning frameworks is preferred: TensorFlow, Scikit-Learn, or AWS Sage Maker
Experience doing Machine Learning on the Cloud
Experience with the following distributed compute and stream analytics platforms is preferred Hadoop, Apache Spark, Apache Storm, Apache Kafka
Moody's is an essential component of the global capital markets, providing credit ratings, research, tools and analysis that contribute to transparent and integrated financial markets. Moody's Corporation (NYSE: MCO) is the parent company of Moody's Investors Service, which provides credit ratings and research covering debt instruments and securities, and Moody's Analytics, which offers leading-edge software, advisory services and research for credit and economic analysis and financial risk management. The Corporation, which reported revenue of $4.2 billion in 2017, employs approximately 11,900 people worldwide and maintains a presence in 41 countries. Further information is available at www.moodys.com.
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Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.