h3bCredit Decision Scientist /b /h3 pCRNCY · Senior · Remote in Latam · USD contractor /p h3bWhy this work matters /b /h3 pAcross the developing world, access to credit still depends on paperwork most people can't produce. A teacher six years in the same job. A vendor who has run the same stall for a decade. Creditworthy, both — and illegible to a system built for someone else. /p pCRNCY exists to close that gap, using technology to open doors for the people who need them most. Every rule you write here decides who gets through. /p h3bMission /b /h3 pHelp CRNCY become the world's best underwriter of credit risk using unstructured and alternative data. We operate in markets where customers often have limited traditional credit information. Our objective is to make better lending decisions under uncertainty and continuously improve risk-adjusted profitability. /p h3bWhat You'll Do /b /h3 ul liAnalyze portfolio performance and identify opportunities to improve profitability through credit strategy. /li liModel the probability of repayment, default and fraud from incomplete and alternative data, and build the statistical inference behind it. /li liTurn that analysis into the credit rules themselves: approval strategy, underwriting requirements, first-loan sizing and customer segmentation. /li liOptimize underwriting requirements and reduce unnecessary customer friction. /li liDesign and assess experiments to improve lending outcomes. /li liQuantify trade-offs between growth, risk, customer experience and profitability. /li liTranslate analysis into practical underwriting and portfolio recommendations. /li /ul pbYou do this work yourself. /b There is no analytics team to delegate to. You frame the question, build the analysis, and own the decision that comes out of it. /p h3bWhat We're Looking For /b /h3 pExperience 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. /p pbExperience in consumer lending or credit is not required. /b We are far more interested in exceptional decision-makers than in experience in any particular industry. /p pWe are interested in candidates who have: /p ul liUsed data and probabilistic reasoning to make or influence important business decisions. /li liEvaluated trade-offs between competing objectives under uncertainty. /li liApplied analytical judgment rather than relying solely on predefined rules or models. /li liTranslated analysis into practical business decisions and recommendations. /li libBeen accountable for the business outcomes of those decisions, not simply the quality of the analysis. /b /li /ul pbWorking capability, hands‑on: /bstatistical 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. You write your own code. /p h3bRequired Academic Background /b /h3 pA degree from a strong university in a quantitative discipline: Decision Science, Operations Research, Applied Mathematics, Statistics, Economics, Engineering, or Computer Science with significant quantitative coursework. /p pYour training should have covered probability and statistics,



decision‑making under uncertainty, optimization, mathematical modeling, econometrics, operations research or risk analysis. /p pAbove all, we are looking for someone who naturally thinks probabilistically — comfortable making decisions with incomplete information, weighing uncertainty, and updating their judgment as new evidence becomes available. /p pbLanguage: /bfluent English and Spanish. Both required. /p h3bWhat This Role Is Not /b /h3 pThis is not: /p ul liA Machine Learning Engineer role /li liA Data Engineering role /li liAn AI Infrastructure role /li liA Machine Learning Research role /li libA traditional Data Scientist role focused primarily on model development /b /li /ul pCandidates whose experience is primarily centered on building models, pipelines, platforms or technical infrastructure will not be considered. /p pWhat we are screening out is the candidate whose output is a model. Here, the output is a decision — you simply have to build the analysis yourself to get there. /p h3bHow We Work /b /h3 ul libHonest and direct. /b Feedback here is unvarnished and immediate. You'll get it, and we expect it back. /li libUnafraid to fail. /b Most of what you test won't work. We would rather run the experiment and find out than defend a rule nobody has questioned. /li libCommitted to excellence. /b High standards, applied to ourselves before anyone else. /li libDedicated to the customer. /b The person on the other side of the decision is the reason the work matters. /li /ul h3bThe Setup /b /h3 ul libUSD contractor. /b Fully remote, location‑flexible, with meaningful daily overlap with the Americas. /li liYou'll work directly with our credit and finance leadership and with the founder. Short path from analysis to decision. /li liReal ownership from day one, across multiple markets. /li /ul #J-18808-Ljbffr

📌 Credit Decisioning Scientist (Italia)
🏢 CRNCY Group
📍 Italia