Required Knowledge and Skills:

• MS or PHD degree preferred in statistics, applied mathematics, or computer science (machine learning)
• 4+ years with predictive modeling techniques and experience in leading predictive modeling initiatives
• 2+ years of management experience
• Ability to break down complex business and technical problems into opportunities for analytical study
• Extensive knowledge and experience in data science, including expertise in one or more of: machine learning, big data/data mining, statistics, business/customer intelligence, data modeling, databases, data warehousing, or a similar field.
• Business application of the following techniques hierarchical Bayesian, Markov chain Monte Carlo, random forests, generalized boosted models, generalized additive models, neural networks, time-series forecasting, game theory, conditional probabilities or other similar approaches
• Deep knowledge of statistical areas such as ANOVA, multiple regression, timeseries modeling, principal component analyses, decision trees, clustering, etc.
• Experience programming in R, SQL, Python
• Automate data wrangling, iterative solution search and operationalization of models, working alongside data architects.
• The ability to handle missing data through an algorithmic approach such as multiple imputations to enable insights in sparse and messy datasets
• Significant experience coding and maintaining predictive algorithms
• Superior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses
• Fluency with analytics platforms like SAS, DSX or SPSS, Data Robot, Alteryx, etc.
• Exceptional troubleshooting skills and thriving in high-expectation scenario with many stakeholders.