Senior Quant Analytics & Insights Lead

Aumni; Jersey City (NJ); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Health care coverage

Retirement savings plan

On-site health centers

Tuition reimbursement

Mental health support

Job summary

JPMorgan Chase is seeking a Sr Quant Associate to join the Commerce Enablement Analytics team within the Data and Analytics organization. You will partner with Product Owners to deliver descriptive, diagnostic, predictive and prescriptive analytics focused on controls, risk and regulatory areas, shaping how and when to engage customers with well-defined metrics and data sources.

Key responsibilities include translating business needs into robust data models, producing high-quality data points,

Qualifications

• Bachelor's degree or higher in a quantitative field with 3+ years analytics experience.
• Experience translating business needs into data models and reports.
• Strong data wrangling, data quality, and storytelling with data.

Responsibilities

• Translate business needs into data models and long-term solutions.
• Create data points to ensure high data quality and reduce redundancy.
• Collaborate with product, data management, strategy and technology teams across units.
• Translate data into actionable insights for stakeholders.
• Production, optimization and automation of recurrent reports.

Skills

Analytical thinking

Communication skills

Problem solving

Initiative

Organizational skills

Education

Bachelor's degree in a quantitative field

Tools

SQL

Alteryx

Tableau

Adobe Analytics

AWS

Snowflake

Oracle

JIRA

Confluence

Job description

JPMorgan Chase is seeking a Sr Quant Associate to join the Commerce Enablement Analytics team within the Data and Analytics organization. You will partner with Product Owners to deliver descriptive, diagnostic, predictive and prescriptive analytics focused on controls, risk and regulatory areas, shaping how and when to engage customers with well-defined metrics and data sources.

Key responsibilities include translating business needs into robust data models, producing high-quality data points,