Description This individual will be responsible for providing quantitative analytic support for Huntington’s Card Product Portfolios (Credit and Debit Card) through marketing campaign development and analysis, Credit Risk monitoring and overall portfolio performance analysis. The role will entail analyzing trends and developing insights with an eye towards strategy enhancement. Responsible for using statistical methodology to ensure that testing, learning and production goals are met. • Develop recommendations to optimize new account acquisition strategies by utilizing statistical scoring, segmentation and regression and simulation techniques • Translate complex data from multiple sources, formats and data structure into actionable and tangible strategies • Coaches, develops and leads junior analysts in business analysis, data extraction projects and reporting • Leverages strong storytelling skills to uncover and communicate trends to all levels of the organization • Apply machine learning, data mining, and visualization techniques to make accurate and actionable analyses in a timely fashion. • Balances sound risk management practices with portfolio growth and profitability • Maintains outlook on competitive landscape and translates to potential opportunities within the Bank's portfolio • Collaborates closely with multiple levels of senior management and various business segments (Marketing, Risk Management, Product, Legal, Regulatory Compliance) to make recommendations and influence business decisions Basic Qualifications • Bachelor’s Degree in business information systems, computer science, mathematical disciplines, finance, economics, or another technical degree. • Minimum of 4+ years of experience in financial services • Minimum of 4+ years of experience using data manipulation tools such as SAS, SQL, R, or Python, Business Objects, or other tools to query large databases and manipulate large data files. • Experience developing and applying statistical or machine learning methods in a corporate environment through applications such as R, python, SAS, SPSS, S, S-PLUS, or Stata Preferred Qualifications: • Credit card lifecycle experience preferable • Experience developing and executing sophisticated credit card marketing analytics, establishing a framework for the delivery of marketing insights and reporting • Advanced degree (ie MBA, MS or PhD) preferred • Experience with business intelligence and data mining tools such as BusinessObjects, Microstrategy, Tableau, Qlickview, and SAS Enterprise Guide/Miner in a corporate or academic environment.. • Strong leadership skills and ability to think independently • Ability to multi-task, remain objective and goal-focused under pressure • Ability to think analytically and strategically and balance quantitative methodology and business insights to drive results • Strong verbal, written and communication skills and ability to convey and simplify complex problems and solutions • Proficiency with Microsoft Office product suite (Excel, Word, Powerpoint) #LI-Hybrid Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay) Yes Workplace Type: Hybrid Huntington is an equal opportunity and affirmative action employer and is committed to providing equal employment opportunities for all regardless of race, color, religion, sex, national origin, age, disability, sexual orientation, veteran status, gender identity and expression, genetic information, or any other basis protected by local, state, or federal law. Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details. Agency Statement: Huntington does not accept solicitation from Third Party Recruiters for any position
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Job Type
Fulltime role
Skills required
Python
Location
Detroit, MI
Salary
No salary information was found.
Date Posted
October 8, 2024
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The Credit Card Quantitative Analyst at Huntington will provide quantitative analytic support for credit and debit card portfolios, focusing on marketing campaign development, credit risk monitoring, and portfolio performance analysis. This role requires strong statistical skills and the ability to translate complex data into actionable strategies.