Job Description:
• Support the design and monitoring of Card underwriting strategies, credit line increase programs, and portfolio performance metrics.
• Analyze performance of underwriting strategies and identify opportunities to improve accuracy and reduce losses.
• Execute and monitor recurring credit strategy programs such as credit line increases, acquisition campaigns, and prescreen processing.
• Support champion/challenger tests and experiment design for various lifecycle credit strategies.
• Assist in designing exposure limits, eligibility rules, and acquisition criteria.
• Query, clean, and analyze large datasets using SQL and Python.
• Design data assets and dashboards to track customer behavior and credit performance.
• Build automations of routine data and reporting processes.
• Perform EDA, feature engineering, advanced segmentation, and data quality checks to gain insights and improve predictive attributes.
• Evaluate alternative data sources (such as open-banking data) and help design business processes to incorporate into decisioning flows.
• Assist in managing and tracking credit risk model performance.
• Partner with Product/Engineering to implement updates to policies and decisioning logic.
• Translate analytical findings into clear recommendations for credit policies.
• Create robust documentation of credit strategies and decisioning workflows.
• Support the coordination of various initiatives with credit bureaus.
• Package insights into crisp narratives and presentations for stakeholders.
Requirements:
• Degree in Computer Science, Statistics, Economics, Finance, or related area. An advanced degree is a plus.
• 4+ years of experience in credit card credit risk analytics. Fintech experience is a plus.
• Experience working with credit bureau data for modelling, segmentation, and benchmarking.
• Experience with customer targeting and prescreen campaigns.
• Bonus points for subprime market experience or exposure to alternative credit data.
• Proficiency in SQL and Python (or similar tools).
• Familiarity with data automation tools such as AWS Glue, Airflow, and DBT.
• Experience with visualization tools such as Tableau (strongly preferred), Power BI, Looker.
• Strong skills with Excel or Google spreadsheets.
• Exposure to experimentation design and tracking.
• Experience cleaning, joining, and analyzing large datasets in a cloud data warehouse environment (i.e. Snowflake, BigQuery, Redshift).
Benefits:
• Company equity in the form of Stock Options
• Performance-based bonuses
• Generous employer-paid health, vision and dental insurance coverage
• Flexible vacation policy
• Educational assistance
• Free gym membership
• Casual dress code
• Team building events and activities
• Remote work arrangements/ flexible work schedule
• Paid parental leave