Join our Card Data and Analytics Team to shape credit card strategies and advance your analytics career.
As a Data Scientist Associate Senior in the Card Data and Analytics Team, you will manage analytics projects for the Slate portfolio, delivering insights and solutions that influence risk, marketing, and finance decisions. You will collaborate with cross-functional teams and present actionable recommendations to senior leadership.
Job responsibilities
- Leads and delivers complex data science projects across risk, marketing, and finance for the Slate product
- Develops, validates, and implements risk models to support credit decisioning and portfolio management
- Analyzes portfolio performance, customer segmentation, and campaign effectiveness to inform strategies
- Manages the end-to-end lifecycle of analytical projects, from proposal to presentation of findings
- Designs and evaluates experiments to measure the impact of risk and marketing initiatives
- Partners with business, risk, and finance teams to identify impactful projects and influence decisions
- Contributes to a positive, inclusive, and high-performing team environment
Required qualifications, capabilities, and skills
- Bachelor's or Master's degree in a quantitative field such as Statistics, Economics, Finance, Business Analytics, Mathematics, Engineering, or Computer Science
- Six years industry experience in portfolio analytics, data science, or business analytics roles within financial services
- Experience building and validating risk models or working in risk strategy for cards portfolios
- Hands-on experience with analytics platforms, languages, and tools such as SAS, SQL, and Python, including big data platforms
- Strong quantitative and problem-solving skills with proficiency in business analytics methods
- Excellent communication skills to convey complex information to business partners and senior leadership
- Results-oriented with strong attention to detail and ability to manage multiple priorities in a fast-paced environment
Preferred qualifications, capabilities, and skills
- Experience with advanced modeling techniques such as machine learning and predictive analytics for risk and marketing
- Familiarity with portfolio management, P&L drivers, and regulatory requirements in the cards business
- Experience with data visualization tools such as Tableau
- Experience with ETL platforms such as Alteryx
