Quant Analytics Senior Associate – Pricing Analytics

Job Description

Quant Analyst- Senior Associate | JPMorgan Chase

The Tone:
This is a full-time role at JPMorgan Chase. The company unifies diverse talent to transform business outcomes through data governance, strategy, reporting, and advanced analytics. This role is critical in defining, refining, and delivering set goals for the pricing business, while also implementing essential technology solutions across various business functions to achieve the firm’s objectives.

The TL;DR
• Role: Full Time
• Type: Full-time

• Team: Consumer & Community Banking Data & Analytics team
• Mission: Define, refine, and deliver pricing business goals and implement critical technology solutions.
• Tech Stack: Python, SQL, Tableau, Alteryx, SAS, R, AWS, Spark/EMR, ChatGPT, Confluence, Snowflake

What You’ll Actually Do
• Deliver: Provide effective quantitative problem solving and analytical research for key pricing initiatives.
• Lead: Guide, mentor, hire, and develop a high-performing team of analytics professionals, fostering scientific rigor and continuous learning.
• Partner: Collaborate with cross-functional teams, including Finance and Marketing, to drive impactful results.
• Analyze: Conduct extensive analysis of pricing functionality, settings, and customer behavior to improve strategies using advanced research and quantitative techniques.
• Own: Support strategic pricing initiatives, including evaluating effectiveness and performing profit & loss analysis to quantify significance.

The Must-Haves
• Background: Graduate or post-graduate degree in a quantitative discipline such as Computer Science, Statistics, Mathematics, Finance, Economics, Data Analytics, or Machine Learning.
• Experience: 3+ years of hands-on analytics experience in banking strategic analytics, along with Python, SQL, and visualization tools including Tableau & Alteryx.
• Skills: Strong statistical and econometric foundation with hands-on experience in pricing analytics, including elasticity estimation, A/B testing, causal inference, and experimentation frameworks, alongside excellent communication abilities to explain complex models.
• Bonus: Professional experience with AWS, Spark/EMR, ChatGPT, Confluence, and Snowflake, exposure to enterprise AI enablement or LLM-assisted workflows, people leadership experience, and a good understanding of IT processes and databases.