AVP-level data analytics role in financial services, driving insights for customer growth and operational improvements. Collaborate with strategy and technology teams to enhance decision making.
Responsibilities
Partner with Acquisition and Account Management (transactional) strategy teams to identify opportunity areas for customer growth/retention, improve existing credit and customer decisions, loss mitigation; proactively detect anomalies and diagnose drivers using existing reporting and performance monitoring
Translate business questions into analytical problem statements, hypotheses, and success metrics; define test design and measurement approach in partnership with stakeholders
Perform data extraction, preparation, feature/variable creation, segmentation, deep-dives, trend analysis, and pattern recognition; apply ML/advanced analytics techniques when appropriate to generate actionable insights
Develop clear, executive-ready narratives, including impact sizing, trade-offs, and recommended actions to enable prioritization and decisioning
Support piloting by providing targeting logic, monitoring/measurement frameworks, and post-test readouts; iterate based on results
Collaborate with model development teams on feature ideas and analytical findings; partner with Technology/Data teams to address data gaps, improve data quality, and enable implementation/monitoring capabilities
Requirements
Bachelor’s degree and 4+ years of experience in data analytics/strategy within Credit, Marketing, Risk or Collections in Financial services, or in lieu of a Bachelor's degree, 6+ years of data analytics/data sciences in Marketing, Risk or Collections in Financial services
Strong understanding of the consumer lending lifecycle and card programs
Demonstrated experience delivering analytics or data science solutions in a strategy, risk, or decisioning environment
Strong analytical toolkit: SQL and SAS ; working knowledge of Python (or similar) for analysis/ML; experience with experimentation/measurement and data visualization/storytelling
Expert-level proficiency in Excel with strong problem-solving skills
Ability to work independently, manage multiple priorities, and deliver in ambiguity and time-sensitive environments
Strong stakeholder management and communication skills; ability to influence without authority
Familiarity with decisioning frameworks, strategy/policy testing, and KPI design
Familiarity with modeling approaches (e.g., logistic regression, tree-based methods/ensembles, neural networks) and how to apply them to business problems
Experience building scalable analytical assets (repeatable code, standardized metrics, dashboards) and monitoring
Strong written and verbal communication skills with the ability to synthesize complex analysis for senior audiences
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