Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master's, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis.
3 years of direct management experience.
Strong communication skills; demonstrated ability to interpret and translate complex technical information to diverse audiences.
Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.) commonly associated with delivery of Data Science solutions.
Experience in developing and reviewing modeling solutions based on broad range of techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
Demonstrated ability to apply best practices in modeling and machine learning techniques to solve business problems.
Demonstrated ability to write and review complex technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences.
A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization.

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