Loss Forecasting Manager

Inizio Partners Corp • Wilmington, DE

1d • Hybrid

About The Position

Candidate should have significant experience in US credit card industry, in Loss forecasting or Credit Policy strategy space. Candidate should demonstrate good communication skills, working with various clients and the ability to clearly articulate forecasts, reasons for forecasts and how they tie to recent trends and macro-economic conditions. We are looking for someone who can play a strategic analytics role supporting Loss forecasting workstream. Specifically, someone with strong first-line risk experience — focused on policy and portfolio analytics. From a skill standpoint, the individual should be able to assess and articulate portfolio impacts arising from changes in first-line drivers. For example: Impact of tightening or expanding Credit Line Management programs Sensitivity to student loan trends Changes in risk appetite framework due to debt sale dynamics Ideal candidate will be able to connect policy actions to portfolio outcomes — work that is forecasting-adjacent and aligned with the projects our team has been driving.

Requirements

• Strong proficiency in vintage models, roll rate models, and stochastic time series models
• US credit cards experience in credit risk
• Credit cards policy experience (Acquisition credit policy preferred, ECM acceptable)
• Hands-on coding in Python & SQL

Responsibilities

• Ability to deliver clear, structured, and concise summaries of complex situations for senior stakeholders
• Consulting-style articulation is essential – distilling what happened, why it matters, and what actions are recommended
• Strong emphasis on credit policy integration, ensuring recommendations align with established frameworks.
• Skilled in synthesizing key insights into crisp narratives and executive-ready presentations
• Translate credit policy decisions into portfolio forecasts
• Should be conversant with maturation, impact of policy change on loss trajectory
• Project and track actuals, explaining variances against the forecast including underlying drivers of change
• Work with a range of models, including vintage-driven, stochastic and challenger orthogonal models

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed