Quant Analytics Senior Associate - Credit Card Installment
On-siteWilmington, Delaware, United States
Job Summary
Deliver quantitative research and pricing analytics to inform strategy, experimentation, and performance measurement by applying advanced statistical techniques to evaluate pricing approaches and understand customer behavior. Lead, mentor, and develop a high-performing analytics team while promoting scientific rigor and ethical artificial intelligence. Conduct extensive analysis of pricing functionality, configuration, and customer behavior to improve strategies, and execute hypothesis testing and advanced experimental design to measure pricing strategy impact. Partner with cross-functional teams to translate findings into decisions and design scalable analytics processes. Own strategic pricing initiatives, including effectiveness evaluation and profit and loss analysis.
Required Qualifications
- Graduate or post-graduate degree in a quantitative discipline (for example, Computer Science, Statistics, Mathematics, Finance, Economics, Data Analytics, or Machine Learning)
- 3+ years of hands-on analytics experience in banking strategic analytics
- Hands-on proficiency with Python and SQL; experience with visualization tools (for example, Tableau) and analytics tools (for example, Alteryx)
- Strong statistical and econometric foundation with hands-on pricing analytics experience, including elasticity estimation, A/B testing, causal inference, and experimentation frameworks
- Strong advanced analytics skills using SAS, Python, or R
- Excellent communication skills with the ability to translate complex models into clear explanations and 'reason codes,' influencing cross-functional stakeholders and senior leadership
- Exposure to enterprise artificial intelligence enablement, large language model-assisted workflows, or analytics transformation programs
- Ability to evaluate opportunities to apply artificial intelligence, generative artificial intelligence, and intelligent automation to improve investigative analysis, control documentation, operating procedures, knowledge retrieval, issue summarization, and workflow efficiency
- Familiarity with supervised learning, anomaly detection, semi-supervised learning, clustering, feature stores, calibration and threshold optimization, imbalanced learning, and pricing sensitivity evaluation
Desired Qualifications
- Proficiency in extract, transform, load processes across structured and unstructured data sources
- Professional experience with Amazon Web Services, Apache Spark, Amazon EMR, Snowflake, Confluence, and generative artificial intelligence tools (subject to firm-approved usage)
- People leadership experience, including recruiting, coaching, performance management, and fostering an inclusive, high-accountability culture
- Strong understanding of information technology processes and databases, with the ability to work directly with data owners and custodians
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