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VP of Data Science

Company: Fin'l Services General, New York, NY
Location: New York
Posted on: May 17, 2018

Job Description:

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 Qualifications 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

Keywords: Fin'l Services General, New York, NY, New York, VP of Data Science, Executive, New York, New York

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