Quant Analyst- Senior Associate
JPMorgan Chase · New York, United States · 1mo ago
SeniorOn-siteQuant Research & Development
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
Join a team that unifies diverse talent to transform business outcomes through data governance, strategy, reporting, and advanced analytics.
As a Quant Analytics Senior Associate within the Consumer & Community Banking Data & Analytics team, you will be focused on defining, refining and delivering set goals for pricing business and responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objective.
Job 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
Required Qualifications, Capabilities, and Skills
- 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
Preferred qualifications, capabilities, and skills
- Proficient in big data ETL processes for structured and unstructured databases
- Professional experience with AWS, Spark/EMR, ChatGPT, Confluence, and Snowflake
- Exposure to enterprise AI enablement, LLM-assisted workflows, or analytics transformation programs and workflows.
- People leadership: recruiting, coaching, performance management, and fostering an inclusive, high-accountability culture.
- Good understanding of IT processes and databases, with ability to work directly with data owners and custodians