AVP, Strategy Sciences

Role Overview

• 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
• Demonstrated project organization skills (workflow, timelines, dependencies) across multiple concurrent efforts
• Familiarity with consumer and/or commercial lending products and practices.

Tech Stack

• Python
• SQL

Benefits

• best-in-class employee benefits and programs that cater to work-life integration and overall well-being
• career advancement and upskilling opportunities