Senior Data Scientist

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Nagro Crédito Agro

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🌾 Agriculture

💳 Fintech

💸 Finance

Agriculture • Fintech • Finance

Nagro Crédito Agro is a Brazilian fintech lender focused on providing 100% digital credit and financing solutions tailored to rural producers and agribusiness. The company uses algorithms and artificial intelligence to analyze individualized credit profiles and deliver fast credit decisions (often within 48 hours), offering personalized loan products, digital onboarding, and an emphasis on relationship management for farmers. Nagro operates as a banking correspondent and originator of agricultural receivables investment funds, partnering with licensed financial institutions rather than acting as a bank itself.

📋 Description

• Develop credit risk models that expand the analytical and lending capacity in agribusiness • Define technical approaches, stacks, and standards for model development and analytical pipelines • Document and communicate results clearly and actionably to different audiences and stakeholders • Lead presentations and feedback cycles with internal and external clients • Collaborate with Engineering and Product teams to understand needs and identify modeling-driven improvement opportunities • Explore new variables and data sources to increase the predictive power of models • Evaluate and adopt new techniques and technologies to improve the efficiency and accuracy of risk solutions • Monitor alignment between data science technical decisions and business objectives • Serve as a technical reference for data scientists and analysts, supporting methodological choices and conducting code and model reviews • Lead the evolution of risk model architecture, covering features, validation, monitoring, and MLOps • Assess trade-offs between complexity, performance, interpretability, and model governance • Support technical planning of medium- and long-term analytical initiatives

🎯 Requirements

• Strong command of Machine Learning applied to real-world credit and risk problems, including model validation, bias control, temporal stability, and explainability • Hands-on experience in feature engineering and evaluating variable impact in production environments • Ability to review, refactor, and raise the quality of analytical code with a focus on efficiency and reproducibility • Experience in credit risk modeling • Participation in analytical architecture decisions involving data, models, and pipelines • Proficiency in querying and manipulating databases for model building and validation • Familiarity with Git and Bitbucket • Clear and concise communication skills to present technical results to diverse audiences • Ability to work autonomously and collaboratively in multidisciplinary teams • Plus points: experience with software engineering and ML engineering; a critical perspective on LLMs and AI agents; experience in agile environments; knowledge of Node or Java; Hadoop, Spark/PySpark, or Polars; familiarity with Cloud platforms, preferably GCP • Bachelor's degree

🏖️ Benefits

• Meal/Food allowance • Wellhub (Gympass) • Uniodonto (dental plan) • Flexible benefits card • Childcare assistance • Life insurance • Language tuition assistance • Pet Life and Dog Life • English Pass • Unimed (health plan)