Back
Tier-1 brand, metro location, mid-level experience requirement, but specialized credit analytics skills moderate applicant pool.
Requires domain-specific credit, risk, and fraud analytics experience limiting cross-industry transferability.
Explicit years requirement plus mandatory credit/risk domain experience and technical ML/SAS/Python skills increase filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead strategy science initiatives for Acquisition and Account Management functions to drive sustainable customer growth and optimize portfolio performance.
Apply advanced analytics, machine learning, and experimentation to identify opportunities, influence decision-making, and deliver measurable business outcomes.
Collaborate with senior leaders, cross-functional teams, and model development to translate insights into scalable, data-driven solutions while managing regulatory considerations.
Bachelor's degree in a quantitative discipline with 5+ years experience in strategy, analytics, or data science in consumer financial services (Credit, Marketing, Risk, Fraud, or Collections) or 7+ years in lieu of degree.
Strong proficiency in SQL and SAS; working knowledge of Python or equivalent, automation, data visualization, and conversational AI tools.
Experience applying advanced statistical and machine learning techniques (logistic regression, tree-based models, ensembles, clustering, neural networks) and working with LLMs for Generative and Agentic AI.
Work Experience Required: 5+ years in relevant financial services analytics/strategy; Notice period: Not explicitly mentioned in the JD.
Demonstrated leadership in managing multiple complex data science and strategy initiatives in consumer financial services with cross-functional influence at senior levels.
Expertise across consumer lending lifecycle including acquisition, underwriting, portfolio management, credit line management, fraud, and collections with strategic problem-solving skills.
Experience in advanced analytics, experimentation frameworks, and emerging AI/ML methodologies with ability to deliver scalable, measurable business impact.