Principal Research Scientist [Risk]

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data-artboard-proxy-min-height="246" data-artboard-proxy-max-height="246"> <div class="t396__elem tn-elem tn-elem__8559900041712751011017" data-elem-id="1712751011017" data-elem-type="text" data-field-top-value="76" data-field-left-value="271" data-field-height-value="130" data-field-width-value="636" data-field-axisy-value="top" data-field-axisx-value="left" data-field-container-value="grid" data-field-topunits-value="px" data-field-leftunits-value="px" data-field-heightunits-value="px" data-field-widthunits-value="px" data-field-textfit-value="autoheight" data-field-top-res-320-value="73" data-field-left-res-320-value="10" data-field-width-res-320-value="306" data-field-top-res-480-value="72" data-field-left-res-480-value="80" data-field-width-res-480-value="319" data-field-top-res-640-value="56" data-field-left-res-640-value="66" data-field-width-res-640-value="501" data-field-top-res-960-value="76" data-field-left-res-960-value="152" data-fields="top,left,width,height,container,axisx,axisy,widthunits,leftunits,topunits"> <div class="tn-atom"> <div id="rec855990004" class="r t-rec" data-animationappear="off" data-record-type="396"> <div class="t396"> <div class="t396__artboard rendered" data-artboard-recid="855990004" data-artboard-screens="320,480,640,960,1200" data-artboard-height="246" data-artboard-valign="center" data-artboard-upscale="grid" data-artboard-height-res-320="363" data-artboard-height-res-480="356" data-artboard-height-res-640="241" data-artboard-height-res-960="246" data-artboard-proxy-min-offset-top="0" data-artboard-proxy-min-height="246" data-artboard-proxy-max-height="246"> <div class="t396__elem tn-elem tn-elem__8559900041713519411346" data-elem-id="1713519411346" data-elem-type="text" data-field-top-value="40" data-field-left-value="271" data-field-height-value="20" data-field-width-value="656" data-field-axisy-value="top" data-field-axisx-value="left" data-field-container-value="grid" data-field-topunits-value="px" data-field-leftunits-value="px" data-field-heightunits-value="px" data-field-widthunits-value="px" data-field-textfit-value="autoheight" data-field-top-res-320-value="40" data-field-left-res-320-value="10" data-field-width-res-320-value="261" data-field-top-res-480-value="40" data-field-left-res-480-value="81" data-field-width-res-480-value="318" data-field-top-res-640-value="29" data-field-left-res-640-value="60" data-field-width-res-640-value="307" data-field-top-res-960-value="40" data-field-left-res-960-value="152" data-fields="top,left,width,height,container,axisx,axisy,widthunits,leftunits,topunits"> <h3>About Plata</h3> <p>Plata is one of the fastest-growing fintech companies in the world. In just 3 years, we've grown to 3M+ customers and reached a $5B+ valuation.&nbsp; We're now strengthening our Risk &amp; Decisioning core team and are looking for a Principal AI Engineer to set the technical bar and build best-in-class, production-grade models that materially move business metrics.</p> <p>&nbsp;</p> <h3>Why this role</h3> <ul> <li>You will own our foundation model program end to end - from research direction to models running in production and driving real credit decisions.</li> <li>Your models directly move the numbers that matter: cost of risk, approval rates, and portfolio NPV across a fast-scaling credit portfolio.</li> <li>You'll work with one of the richest financial datasets in LATAM billions of transactions and behavioral events across 3M+ customers, growing daily.</li> </ul> <h3>Challenges that await you</h3> <ul> <li>Build an end-to-end <strong>foundation model</strong> over financial event sequences - transactions, credit bureau data, and in-app behavioral events&nbsp; with subsequent fine-tuning for downstream business tasks: underwriting (PD), credit limit strategy, fraud detection, collections, and propensity models.</li> <li>Drive technical decisions end-to-end: methodology → implementation → performance and latency → robustness, interpretability, and regulatory compliance.</li> <li>Take models from research to production: training infrastructure, evaluation frameworks, model serving, latency/cost optimization, and monitoring.</li> <li>Research state-of-the-art approaches in the industry, publish your own work, and speak at leading conferences.&nbsp;</li> <li>Mentor senior engineers and scientists; own technical standards for model development across the team (design reviews, evaluation methodology, deployment practices).</li> <li>Communicate results clearly to cross-functional stakeholders: product, risk, business, and leadership.</li> </ul> <h3>What makes you a great fit</h3> <ul> <li>Proven experience applying deep learning to <strong>sequential data</strong> - transformer architectures on event/transaction sequences strongly preferred, but not required.</li> <li>Strong foundation in mathematical statistics and probability theory.&nbsp;</li> <li>Deep understanding of machine learning algorithms (GBM, MLP, CNN, RNN, Transformers, etc.)</li> <li>Experience taking large models to production: distributed training, model serving, latency/cost trade-offs.</li> <li>Ability to strike a reasonable balance between solution complexity and practical applicability.</li> <li>Strong mathematical or technical education - degree in mathematics, physics, or CS from a top technical university&nbsp;</li> <li>Kaggle Competitions Master/Grandmaster or equivalent (a plus); experience developing models in banking or consumer lending (a plus)</li> <li>Strong communication skills.</li> </ul> <h3>Our ways of working&nbsp;</h3> <ul> <li><strong>Innovative Spirit: </strong>a commitment to creativity and groundbreaking solutions</li> <li><strong>Honest Feedback:</strong> valuing open, transparent communication</li> <li><strong>Supportive Team: </strong>a strong, collaborative community</li> <li><strong>Celebrating Achievements: </strong>recognizing our wins together</li> <li><strong>High-Tech Environment:</strong> a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances</li> </ul> <h3>Our benefits</h3> <ul> <li>Relocation support to one of our hubs - Mexico, Cyprus, Serbia, Spain&nbsp; with assistance for the employee and their family</li> <li>Flexible work from one of our offices or remote</li> <li>Healthcare coverage</li> <li>Education budget: language lessons, professional training and certifications</li> <li>Wellness budget: mental health and fitness activity reimbursements</li> <li>Vacation policy: 20 days of annual leave and paid sick leave</li> </ul> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>