LTV/NVP Modeling Analyst (Fintech)

TL;DR

LTV/NVP Modeling Analyst (Fintech): Building and maintaining behavioral portfolio models for forecasting, unit economics (NPV/LTV), and strategy decisions with an accent on cohort/term-based hazard & transition curves. Focus on validating models and assumptions (back-testing, stability/drift, segmentation, bootstrap bounds) and implementing strong data-quality controls.

Location: Remote: Armenia

Company

hirify.global is a rapidly expanding fintech company serving thousands of customers in the Philippines through our lending business.

What you will do

• Build and maintain behavioral portfolio models (delinquency/default dynamics) for forecasting, unit economics (NPV/LTV), and strategy decisions.
• Develop cohort/term-based hazard & transition curves and ensure correct alignment of hazard vs cumulative definitions and consistent monitoring.
• Validate models and assumptions (back-testing, stability/drift, segmentation, bootstrap bounds) and implement strong data-quality controls.
• Produce clear documentation and stakeholder-ready outputs (methodology notes, model cards, dashboards/presentations).

Requirements

• Bachelor’s or Master’s degree in Mathematics, Statistics, Economics, Computer Science, or a related field.
• Proven 3+ years of experience in credit risk/portfolio analytics/lending analytics (fintech, bank, MFI).
• Strong knowledge of financial risk management principles, methodologies, and portfolio performance modeling.
• Experience with unit economics: NPV / LTV, cashflow modeling, prepayment & early repayment, restructuring behavior, discounting assumptions.
• Hands-on Python (pandas/numpy/statsmodels/sklearn); ability to write production-quality research code and notebooks.
• SQL (confident joins, window functions, large datasets); ability to work with messy raw data and define clean features/metrics.
• Solid statistics: logistic regression/calibration, confidence intervals/bootstrapping, model validation, bias/leakage control.

Culture & Benefits

• We review applications on a rolling basis and aim to get back within 2–3 business days.