Principal Research Scientist [Risk]
Banco Plata, S.A., Institución de Banca Múltiple
WorldwideremotePosted 4 days ago
Skill Required
Research-ScientistMachine-Learning-ScientistAI-Research-ScientistRisk-ModelerPrincipal-EngineerPrincipal-Research-ScientistDirector-Of-Risk-Research-And-DevelopmentPrincipal-ScientistRisk-Analytics-ScientistSenior-Research-ScientistSenior-Principal-ScientistSenior-Model-Risk-ScientistData-ScienceMachine LearningDeep LearningStatisticsdevelopingObservabilityData Structuresfintechetc.)designandAIFulltime
Key highlights
- Principal level experience
- Relocation support to Mexico, Cyprus, Serbia, or Spain
- Degree from a top technical university required
- Focus on foundation models for financial event sequences
Role overview
Plata is one of the fastest-growing fintech companies in the world, having reached 3M+ customers and a $5B+ valuation in 3 years. They are seeking a Principal AI Engineer for their Risk & Decisioning core team to set the technical bar and build production-grade models that materially move business metrics. In this role, you will own the foundation model program end-to-end—from research direction to production—utilizing one of the richest financial datasets in LATAM to influence cost of risk, approval rates, and portfolio NPV.
Responsibilities
- 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.
Requirements
- Proven experience applying deep learning to sequential data.
- 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
- Strong communication skills.
Nice to have
- Transformer architectures on event/transaction sequences strongly preferred, but not required.
- Kaggle Competitions Master/Grandmaster or equivalent (a plus)
- Experience developing models in banking or consumer lending (a plus)
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
Additional details
- 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
- Originally posted on Himalayas