Research Scientist [Risk]

About Plata 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. We're now strengthening our Risk & 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. Why this role You will own our foundation model program end to end - from research direction to models running in production and driving real credit decisions. Your models directly move the numbers that matter: cost of risk, approval rates, and portfolio NPV across a fast-scaling credit portfolio. You'll work with one of the richest financial datasets in LATAM billions of transactions and behavioral events across 3M+ customers, growing daily. What you'll do Build an end-to-end foundation model over financial event sequences - transactions, credit bureau data, and in-app behavioral events with subsequent fine-tuning for downstream business tasks: underwriting (PD), credit limit strategy, fraud detection, collections, and propensity models. Drive technical decisions end-to-end: methodology → implementation → performance and latency → robustness, interpretability, and regulatory compliance. Take models from research to production: training infrastructure, evaluation frameworks, model serving, latency/cost optimization, and monitoring. Research state-of-the-art approaches in the industry, publish your own work, and speak at leading conferences. Mentor senior engineers and scientists; own technical standards for model development across the team (design reviews, evaluation methodology, deployment practices). Communicate results clearly to cross-functional stakeholders: product, risk, business, and leadership. What makes you a great fit Proven experience applying deep learning to sequential data - transformer architectures on event/transaction sequences strongly preferred, but not required. Strong foundation in mathematical statistics and probability theory. Deep understanding of machine learning algorithms (GBM, MLP, CNN, RNN, Transformers, etc.) Experience taking large models to production: distributed training, model serving, latency/cost trade-offs. Ability to strike a reasonable balance between solution complexity and practical applicability. Strong mathematical or technical education - degree in mathematics, physics, or CS from a top technical university Kaggle Competitions Master/Grandmaster or equivalent (a plus); experience developing models in banking or consumer lending (a plus) Strong communication skills. Our ways of working Innovative Spirit: a commitment to creativity and groundbreaking solutions Honest Feedback: valuing open, transparent communication Supportive Team: a strong, collaborative community Celebrating Achievements: recognizing our wins together High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances Our benefits Relocation support to one of our hubs - Mexico, Cyprus, Serbia, Spain with assistance for the employee and their family Flexible work from one of our offices or remote Healthcare coverage Education budget: language lessons, professional training and certifications Wellness budget: mental health and fitness activity reimbursements Vacation policy: 20 days of annual leave and paid sick leave