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Agibank

Hybrid digital bank offering credit services.

Data Scientist - Credit Modeling

Data ScienceUpdated on Nov 11
Full-timeCampinas - State of São Paulo, BrazilNo salary listed

About the Job

Requirements

  • Experience with programming languages such as Python or R.
  • Proficiency in classical and modern machine-learning algorithms, including decision trees, logistic regression, ensemble methods, and boosting models such as XGBoost, LightGBM, and CatBoost.
  • Strong foundation in statistics, probability, and predictive modeling.
  • Experience manipulating and processing large volumes of data using SQL and Spark.
  • Experience with credit risk models, including PD, LGD, and EAD.
  • Knowledge of MLOps practices and deploying models into production.
  • Experience or interest in generative AI, natural language processing, or large language models.
  • Experience developing and implementing credit-cycle models for application, behavior, and collections.
  • Completed undergraduate degree.

Responsibilities

  • Develop, implement, and monitor statistical and machine-learning models to address complex business problems with business impact.
  • Explore, clean, and prepare data for analytical studies.
  • Create reports that translate technical results into insights for business teams.
  • Collaborate with multidisciplinary teams to formulate hypotheses, understand needs, assess model applications in strategies, test solutions, and track results.
  • Ensure the quality, integrity, and governance of data used in analytical projects.

Desired Qualifications

  • Familiarity with visualization tools such as Power BI, Tableau, or similar tools.
  • Experience in cloud-computing environments such as AWS, GCP, or Azure.
  • Knowledge of code-versioning tools such as Git and continuous integration.

About the Company

Agibank

Hybrid digital bank offering credit services.

Agibank is a Brazilian financial institution that combines a digital banking platform with a network of over 1,000 physical

Company size
5,001-10,000
Company stage
IPO
Headquarters
São Paulo, Brazil
Founded
1999

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