Principal Research Scientist [Risk]✦ anywhere

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.

Challenges that await you

- 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

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Innovative Spirit: a commitment to creativity and groundbreaking solutions

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Honest Feedback: valuing open, transparent communication

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Supportive Team: a strong, collaborative community

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Celebrating Achievements: recognizing our wins together

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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

Originally posted on Himalayas