Overview : Develops and runs and evaluates data science and predictive analytics models to support the marketing analytics function, facilitating contact campaigns and providing data-driven, statistical insights to grow and retain a profitable customer base. Responsibilities : - Designs, codes, implements, and continuously improves ad-hoc and production-level predictive and prescriptive analytical models to help our client maximize ROI on marketing spend, understand customer behavior and grow our customer file. - Communicates findings using visually compelling graphics and clear explanations. - Interfaces with key stakeholders across our client business to gather requirements, suggest approaches, socialize results. - Supports Customer Analytics function on Big Data (i.e. structured and un-structured sources) and analytics initiatives. Qualifications : - Proficiency in predictive/ prescriptive analytics and statistical methods including: regressions, neural networks, Bayesian networks, decision trees, survival modeling, feature engineering, mathematical programming, etc. - Proficiency in data mining, machine learning, or statistical software/programming languages, such as R, Python, SAS, etc. - Ability to understand complex business processes, concepts, and requirements and translate them into mathematical models. - Expertise in Excel and SQL required, experience with data visualization software (e.g. Tableau, QlikView, PowerBI, etc.), visual programming/data mining software (Alteryx, SPSS Modeler, RapidMiner, etc.) and APIs and knowledge of MDM and data architecture a plus. - Willing and able to quickly and effectively learn new software, techniques, and concepts. - 2+ years experience with hands-on business analytics/statistical modeling, especially related to marketing attribution, customer segmentation, lifetime value, and marketing response. - B.S. in the Quantitative discipline such as Mathematics, Statistics, Data Science, Business Analytics, Computer Science, Engineering; M.S. degree or Ph.D. a plus.