Staff Credit Data Analyst – Cards

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