Senior Quant Analytics Lead - Pricing

Next Frontier Capital; New York (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

Chase is seeking a Quant Analytics Senior Associate in the Consumer & Community Banking Data & Analytics team to define and deliver pricing initiatives using advanced analytics. You will guide a high-performing team, apply rigorous statistical methods, and integrate GenAI/LLMs with traditional analytical approaches to drive measurable business outcomes.

The role emphasizes cross-functional partnership with Finance and Marketing, scalable data processes, and a strong emphasis on rigorous

Qualifications

• Graduate or post-graduate degree in a quantitative discipline such as Computer Science, Statistics, Mathematics, Finance, Economics, Data Analytics, or Machine Learning
• 3+ years of hands-on analytics experience in banking strategic analytics along with Python, SQL and visualization tool including Tableau & Alteryx
• Hands on experience in Python, SQL and visualization tool including Tableau with machine learning frameworks
• Strong statistical and econometric foundation with hands-on experience in pricing analytics, including elasticity estimation, A/B testing, causal inference, and experimentation frameworks
• Solid skills in advanced analytics with SAS, Python, or R language
• Excellent communication skills to translate and explain complex models with clear reason codes, influencing cross-functional stakeholders and senior leadership
• Exposure to enterprise AI enablement, LLM-assisted workflows, or analytics transformation programs
• Ability to evaluate opportunities to apply AI, GenAI, or 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/threshold optimization, imbalanced learning, and pricing sensitivity evaluation

Responsibilities

• Deliver effective quantitative problem solving and analytical research for key pricing initiatives
• Apply deep understanding of business and data analytical techniques to research and experimentation
• Lead, mentor, hire, and develop a high-performing team of analytics professionals, promoting scientific rigor, ethical AI, and continuous learning
• Maintain a pragmatic approach to GenAI/LLMs as complementary tools, prioritizing classical/statistical/graph analytical methods for core pricing strategy workstreams
• Partner with cross-functional teams, including Finance and Marketing, to drive impactful results
• Design and implement scalable and reliable data analytics processes to optimize business outcomes
• Conduct extensive analysis of pricing functionality, settings, and customer behavior to improve strategies and policies using advanced research and quantitative techniques
• Own and support strategic pricing initiatives, including evaluating effectiveness and performing profit & loss analysis to quantify statistical and practical significance
• Solve unstructured business problems and develop deep-dive analysis of customer behavior using multiple analytics and statistical techniques
• Conduct hypothesis testing and advanced experimental design, including A/B and multivariate tests, to measure the impact and effectiveness of pricing strategies

Skills

Python

SQL

Tableau

Alteryx

SAS

R

Econometrics

A/B testing

GenAI

LLMs

Education

Graduate or postgraduate degree in a quantitative discipline

Tools

AWS

Snowflake

Spark/EMR

Job description

Chase is seeking a Quant Analytics Senior Associate in the Consumer & Community Banking Data & Analytics team to define and deliver pricing initiatives using advanced analytics. You will guide a high-performing team, apply rigorous statistical methods, and integrate GenAI/LLMs with traditional analytical approaches to drive measurable business outcomes.

The role emphasizes cross-functional partnership with Finance and Marketing, scalable data processes, and a strong emphasis on rigorous