Strategic AI Outcomes Manager
•Jasper Ai· 16h
🏷️ Data Science⏰ Full-time🎯 Lead / Principal💰 $418k-493k🇺🇸 USA
16h ago
Tala·about 1 month ago
We are seeking an experienced, impact-oriented credit leader to own Tala's Expansion Markets risk function, covering our growth D2C markets and our Partnership (B2B2C) underwriting. The candidate will report to the Director of Risk and will be the key analytical and strategic owner for these portfolios - responsible for risk performance monitoring, strategy development and implementation, and cross-functional execution with Product and Data Science squads. A defining element of this role is the ability to translate both current portfolio performance and long-term forward-looking expectations into risk strategy - including in markets where data histories are still maturing and conviction must be built from first principles, lending intuition, and structured judgment rather than established baselines.
The ideal candidate is a strong credit practitioner who combines analytical rigor with strategic instinct and consumer lending intuition. They are equally comfortable synthesizing net new data points into a credible underwriting strategy for a partnership pilot as they are partnering with Product to shape decisioning roadmaps. They thrive in ambiguity, move with urgency, and communicate with precision.
Responsible for understanding portfolio health across the full customer lifecycle and making strategy recommendations accordingly
Develops and executes credit strategies within Tala's decisioning frameworks, including approval rate calibration, limit setting, and pricing
Monitors portfolio KPIs continuously, identifies emerging trends (volume, quality, customer behavior), and translates findings into actionable strategy changes
Develops existing decisioning frameworks to support evolution of portfolio
Partners with Product and Data Science squads to translate risk strategy priorities into decisioning improvements - from feature development to model calibration to A/B test design
Provides concise, well-reasoned portfolio updates to leadership, Finance, and Capital Markets stakeholders
Leads underwriting strategy for partnership pilots and ongoing risk management for Tala's B2B2C portfolio including evaluating net new partner data, assessing its quality, and incorporating into credit policy
Establishes and maintains credit policies tailored to partnership structures, ensuring alignment with Tala's enterprise risk appetite while accounting for partner-specific dynamics (e.g., data availability, regulatory environment, customer profile)
Evaluates new partnership opportunities from a risk perspective, providing structured assessments of underwriting feasibility, expected performance, and risk-adjusted economics
Partners with Data Science on data collection strategies for pilots - balancing what's needed to support future model development and policy design against prudent cost exposure
6+ years of experience in unsecured consumer lending, with hands-on ownership of credit portfolio performance in a high-volume, data-driven environment
Demonstrated ability to develop and execute credit strategies that balance growth and risk - including experience with approval policy, pricing, limit management, and portfolio segmentation
Experience with partnership or B2B2C lending a strong plus; comfort adapting underwriting frameworks to non-standard data environments required
Strong analytical foundation; comfort with ambiguity and indirect data signals when direct data is unavailable
Proactive and inquisitive approach to identifying and surfacing emerging risks and opportunities before they become problems
Clear, precise communicator - able to synthesize complex portfolio dynamics into crisp recommendations for both technical and non-technical audiences
Strong cross-functional instincts; track record of influencing product and engineering partners on credit priorities without direct authority
Proficiency in SQL required; Python preferred
Comfortable working in a fast-paced, global environment with distributed teams across multiple time zones