Credit Decisioning Specialist, Latam – Contract

Job not on LinkedIn

🕒 August 1

🇧🇿 Belize – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

✨ Contract Specialist

👻 Ghost score 38%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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CRNCY (BZ) Limited

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🤝 B2B

💸 Finance

Consulting • B2B • Finance

CRNCY (BZ) Limited, pronounced Currency, is an investment holding company focused on building top tier businesses across medium-sized less competitive markets within the Commonwealth group of countries. Their mission is to develop the most efficient, well-run, and profitable companies within their management portfolio, specializing in business development, project management, information technology, and financial services.

📋 Description

• Analyze portfolio performance and identify opportunities to improve profitability through credit strategy • Model the probability of repayment, default and fraud from incomplete and alternative data, and build the statistical inference behind it • Turn that analysis into the credit rules themselves: approval strategy, underwriting requirements, first-loan sizing and customer segmentation • Optimize underwriting requirements and reduce unnecessary customer friction • Design and assess experiments to improve lending outcomes • Quantify trade-offs between growth, risk, customer experience and profitability • Translate analysis into practical underwriting and portfolio recommendations

🎯 Requirements

• Experience in at least one of: portfolio strategy or analytics, underwriting strategy, lending strategy, risk management, or another analytical role involving high-consequence decision-making under uncertainty • Used data and probabilistic reasoning to make or influence important business decisions • Evaluated trade-offs between competing objectives under uncertainty • Applied analytical judgment rather than relying solely on predefined rules or models • Translated analysis into practical business decisions and recommendations • Been accountable for the business outcomes of those decisions, not simply the quality of the analysis • Working capability, hands-on: statistical inference and probability; causal reasoning and selection bias; practical modeling — logistic regression, scorecards, gradient boosting — with clean validation discipline and no data leakage; experiment design and power; expected-value analysis; segmentation • Python and SQL at analysis-and-modeling level

🏖️ Benefits

• USD contractor • Fully remote, location-flexible, with meaningful daily overlap with the Americas • Real ownership from day one, across multiple markets

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