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Strong employer brand and metro location but niche credit-plus-ML specialization limits applicant density.
Requires deep consumer-lending, credit and risk domain expertise, reducing cross-industry transferability.
Explicit years plus mandatory credit domain experience and specific tools (SQL, SAS, Python, LLMs) make filters strict.
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Lead strategy science initiatives using advanced analytics, machine learning, and experimentation to drive growth and portfolio optimization in Acquisition and Account Management.
Partner with senior leaders and cross-functional teams to identify high-impact opportunities, define strategic priorities, and implement scalable data-driven solutions.
Own executive communication of analytical insights, test-and-learn frameworks, and delivery of measurable business outcomes while mentoring junior team members.
Bachelor's degree in quantitative discipline with 5+ years experience in strategy, analytics, or data science in consumer financial services (Credit, Marketing, Risk, Fraud, or Collections) OR 7+ years analytics experience without degree.
Strong technical skills in SQL, SAS, Python (or similar), and experience with advanced statistical/machine learning techniques.
Experience with consumer lending lifecycle including acquisition, underwriting, portfolio management, and fraud.
Work Experience Required: 5+ years in relevant analytics/strategy roles within financial services as specified.
Proven ability to independently lead complex data-driven strategy projects impacting credit and fraud portfolio performance.
Experience collaborating with senior stakeholders and cross-functional teams (Product, Technology, Model Development) for enterprise initiative delivery.
Demonstrated expertise in designing experimentation frameworks, leveraging emerging AI/ML methods, and translating complex analysis into concise executive communications.