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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythondata analysiscredit risk analyticsfeature engineeringdata cleaningadvanced segmentationEDAdata automationcredit modeling

Soft Skills

analytical skillscommunicationcollaborationproblem-solvingdocumentationpresentation skillsstakeholder managementstrategic thinkingattention to detailcreativity