AmeriSave Mortgage Corporation is seeking to solve complex problems and deliver measurable business outcomes through advanced analytics, optimization, and modeling in marketing analytics, workforce planning, lead routing, and pricing sensitivity.
Requirements
- Strong proficiency in R, Python, SQL, and Power-BI
- Experience working with workforce management systems and call center focused organizations
- Demonstrated success in marketing analytics, workforce optimization, and pricing strategy.
- Experience working with credit bureau data
- Master’s or PhD in Data Science, Statistics, Operations Research, Computer Science, or a related field
- 6+ years of experience in applied data science roles, preferably in high-volume, customer-facing environments
Responsibilities
- Build and deploy predictive models for lead conversion, customer lifetime value, and marketing ROI.
- Design and analyze experiments to evaluate campaign performance and optimize spend.
- Develop attribution frameworks and incrementality testing to guide marketing strategy.
- Design intelligent scheduling systems that align staffing with demand across mortgage and call center operations.
- Apply constraint-based optimization, linear/mixed-integer programming, and fatigue modeling to maximize productivity and SLA adherence.
- Develop machine learning models to optimize lead routing based on agent performance, availability, and customer profiles.
- Analyze pricing elasticity and customer sensitivity to rate changes across segments and channels.
Other
- Master’s or PhD in Data Science, Statistics, Operations Research, Computer Science, or a related field
- 6+ years of experience in applied data science roles, preferably in high-volume, customer-facing environments
- Applicants must be authorized to work in the U.S. without sponsorship
- Partner with stakeholders across Marketing, Sales, Operations, and Finance to translate business needs into analytical solutions
- Present findings and recommendations to senior leadership in a clear, actionable manner
