Senior Applied Data Scientist

Role overview

Shape the modeling work that turns financial data and payment activity into decisions such as risk scores, fraud signals, and transaction categories. As the data science reference on a cross-functional team, you will choose which problems merit modeling, define what good performance means, and take models from investigation through production ownership.

Responsibilities

- Design and select statistical or machine learning approaches for classification, regression, ranking, language, and related tasks; justify choices with evidence. - Work with product and business partners to turn open questions into well-scoped modeling problems and identify useful data signals. - Build pipelines, APIs, or services to run models reliably in production, then monitor performance, drift, and retraining needs. - Design experiments and offline evaluations to determine whether changes improve the intended business outcomes. - Use AI coding and research tools to accelerate exploration, feature testing, pipeline development, and delivery. - Share modeling judgment and raise data science standards across the team.

Requirements

- Strong applied data science and machine learning skills, including the ability to explain and defend modeling decisions. - Ability to connect model design to business context and measurable outcomes. - Engineering capability to productionize models and take responsibility for their operation. - Experience evaluating model behavior, including non-deterministic systems where applicable. - Comfort working with Python and SQL in a cloud data environment.

Nice to have

- Experience with financial data, risk scoring, fraud detection, or transaction categorization. - Experience using large language models in data pipelines, such as for labeling or extraction, and understanding when they are appropriate. - Familiarity with managed cloud machine-learning services, A/B testing, and offline evaluation.

Benefits and work setup

The team is remote-friendly, with offices in Mexico City and São Paulo and at least three shared working hours across time zones. Listed perks include stock options, a company performance bonus, flexible hours, health insurance, paid time off for birthdays, training and wellness budgets, laptop renewal, and team events.