Marketing Analytics Intern

United States·Chicagoentry

OtherMarketing Analytics Intern

3 views0 saves0 applied

Apply Now

Quick Summary

Key Responsibilities

Monitor key funnel metrics through reports and dashboards to track channel performance, diagnose deviations, and surface root-cause insights Use SQL and Python to analyze funnel trends,

Technical Tools

OtherMarketing Analytics Intern

Founded in 2017, NinjaHoldings works to give everyday Americans better access to financial services than traditional institutions typically provide. Through our CreditNinja and NinjaCard brands, we offer digital banking and lending products designed for consumers often overlooked, paired with incentives that support long-term financial improvement. Our Edge brand extends this expertise to other companies, providing underwriting, fraud detection, and analytics services. Headquartered in Chicago with a distributed global workforce, we are a lean, growing organization committed to advancing consumer finance in the US.

NinjaHoldings is seeking an Intern to join our Marketing Analytics team, partnering with Marketing and senior analytics experts. You’ll support the data pipeline—updating Snowflake data models, assisting with Periscope dashboard builds and automations, and using SQL/Python to analyze funnel performance and identify drop-off drivers. Your insights will help inform clear, data-driven recommendations for leadership and guide cross-functional testing and optimizations.

Our internship program offers an opportunity to work on real projects that move the business forward while receiving hands-on professional development.

When: May-August 2027

Location: Hybrid, downtown Chicago HQ (in-office 2x/week). Candidates must be local or able to relocate independently - relocation assistance is not provided.

Schedule: 40 hours/week

Responsibilities

~1 min read

→Currently pursuing a Bachelor’s or Master’s Degree
→Strong written and verbal communication skills with excellent attention to detail.
→Strong ability to write queries for data extraction, transformation, and analysis. Must be comfortable with joins, aggregations, subqueries, CTEs, and window functions.
→Strong quantitative and problem-solving skills with key attention to detail

Nice to Have

~1 min read

Advanced degree in quantitative discipline (e.g., math, statistics, operations research, quantitative finance, physics, engineering, computer sciences, etc.)
Experience supporting and working with cross-functional teams in a dynamic environment
Proficiency using Python