Principal Research Scientist [Risk]
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Job description
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
- 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
Originally posted on Himalayas
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