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Tier-1 brand, metro location, and a generalist early-career data science role attract high candidate density.
Technical modeling skills transfer widely, but payments and campaign analytics preference raises industry specificity.
Explicit Master's degree, 0-2 years, and required SQL/Python/modeling skills increase filtering rigidity.
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Develop analytical solutions and generate actionable insights to drive customer engagement and organic growth strategies for U.S. Small Business customers in Spend, Lend, and Beyond-the-Card segments.
Work within the SBS Engagement Analytics team to utilize data science techniques including SQL, statistical modeling, and experimentation to inform marketing and investment decisions.
Translate complex data analyses into clear business recommendations to support campaign measurement and growth initiatives.
Master's Degree in a quantitative field such as Engineering, Mathematics, Finance, Computer Science, Statistics, or Economics.
0-2 years of professional experience in Data Science and Analytics.
Strong proficiency in SQL and experience with large datasets; experience with Python or similar tools required.
Understanding of Test & Control methodologies, experimentation, campaign measurement, and statistical modeling techniques like XGBoost, clustering, decision trees, and regression.
Experienced in customer engagement analytics, campaign measurement, personalization, or cross-sell/growth analytics to enhance business impact.
Comfortable working with advanced modeling techniques and statistical experimentation to solve unstructured business problems.
Able to effectively communicate technical insights to stakeholders and influence business decisions.