Full-Time Data Scientist II

• Leverage a richly populated feature stores to understand consumer and market behavior. 20%
• Implement a predictive model to determine whether a person or household is likely to open a lending or deposit account based on the advertising signals they've received. 20%
• Derive a set of new features that will help better understand the interplay between geography and audience features to improve model performance. 20%
• Work collaboratively with Data Engineering and Analytics teams to develop new products with applied AI and bring them to market. 20%
• Participate in planning, roadmap, and architecture discussions to help evolve our AI processes to improve revenue-generating products. 20%

• Bachelor’s Degree (Required)
• Master's Degree in a quantitative discipline (Computer Science, Mathematics, Engineering, Statistics) (Required)
• Doctorate Degree (Preferred)

• 5-10 years of experience within the Data Science space.
• In lieu of the stated education and experience requirements, a combination of experience and education will be considered.
• Experience with web or digital analytics tools (e.g. Adobe Analytics, Google Analytics, WebTrends) preferred.

• Conduct in-depth user journey analysis to pinpoint engagement gaps, conversion barriers, and high-performing paths.
• Identify opportunities in print, SEO, paid ads, and digital marketing optimization by using data from POS systems, Google Analytics and media delivery platforms.
• Understanding and experience with Machine Learning workflows and model productionalization.
• Expertise in analysis or design of experiments for standard and adhoc analysis, interpreting results to drive marketing strategies.
• Familiarity with Spark Framework within an On-Premise Big Data Environment.
• Good analytical skills, with expertise in analytical toolkits such as Regression, Tree-based Models, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modeling, and predictive analysis.
• Proficient in Python/PySpark collaborative development in an industry setting.
• Ability to create Data-Driven presentations and reports for technical and non-technical stakeholders.
• Proven track record of leveraging data to optimize marketing campaigns and improve customer engagement.

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