Data Scientist (AI/ML)

Location: Remote from Mexico or Brazil, with offices in Mexico City and São Paulo and at least 3 hours of daily time-zone overlap.

Company

hirify.global is an open finance API platform that provides access to financial data and payment initiation across Latin America.

What you will do

• Design and select statistical and machine learning models for credit risk, fraud detection, transaction categorization, ranking, NLP, and LLM-based use cases.
• Frame ambiguous business questions as well-scoped modeling problems and identify the financial signals that explain target outcomes.
• Use agentic coding and research tools to explore data, test feature hypotheses, build pipelines, and develop model services.
• Productionize and own models through deployment, monitoring, drift detection, retraining, and retirement.
• Design A/B tests and offline evaluations to measure model performance and business impact.
• Partner with Engineering, Product, Data Research, customers, and business stakeholders while sharing practical advances in generative AI.

Requirements

• 5+ years of hands-on experience as a Data Scientist, Applied Scientist, or in a similar modeling role.
• End-to-end production ownership of models, including problem framing, deployment, monitoring, and measurable business impact.
• Strong grounding in statistics and experience comparing multiple model types, including tree-based methods, regression, or deep learning.
• Strong Python data science skills with pandas, scikit-learn, and TensorFlow or PyTorch, plus SQL for data access and feature development.
• Experience with testing, version control, CI/CD, maintainable software, and taking models into production independently.
• Production experience with LLMs, including tool use or agents, retrieval, structured outputs, and evaluation; proficient written and spoken English.

Nice to have

• Experience in fintech, financial risk, regulated data, or customer-facing data science.
• Business, strategy, MBA, consulting, or product experience alongside data science.
• Experience with MLOps, model versioning, monitoring, automated retraining, or AWS managed machine learning services.
• Experience building LLM evaluations, LLM-as-judge systems, or LLM-powered data pipelines.

Culture & Benefits

• Cross-functional, autonomous teams using continuous delivery and a modern technology stack.
• Developer-first products, transparent communication, and a pragmatic, customer-focused working style.
• Remote-friendly work with flexible hours and offices in Mexico City and São Paulo.
• Health insurance, paid time off, birthday leave, wellness stipends, training budget, and bank-holiday flexibility.
• Stock options, annual company bonus, laptop renewal every three years, team events, and yearly company offsites.

Hiring process

• People team chat.
• Take-home challenge followed by a challenge presentation.
• Team fit chat and meeting with the founders.