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Tier-1 brand, metro location, mid-level ML role, and broad skill requirements increase applicant competition.
Core ML and data skills transfer well, but credit-card and regulated finance experience raises domain specificity.
Explicit 7+ years plus mandatory ML, Python, and domain-specific preferences make filters strict.
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Design, implement, and optimize machine learning and statistical models to improve digital marketing, product sales, and customer engagement for US Consumer Cards.
Lead and enhance the 'Test & Learn' framework to enable rapid experiment design, execution, and impact measurement across digital platforms.
Provide data-driven insights to reduce cost-to-serve and improve operational efficiencies across the customer lifecycle.
7+ years of experience in data science, machine learning, or a related field.
Proficient in Python, SQL, and machine learning libraries (scikit-learn, TensorFlow, PyTorch, Transformers); PySpark experience preferred.
Bachelor's degree in a quantitative field (computer science, statistics, mathematics, engineering) required; Master's preferred.
Experience with digital marketing analytics and knowledge of credit card business is highly beneficial.
Experienced in building and deploying scalable machine learning solutions with strong coding practices in Python and related tools.
Strategic thinker with the ability to translate complex analytics into business impact and communicate effectively with senior stakeholders.
Capable of mentoring junior team members and collaborating across cross-functional teams to drive digital growth and efficiency.