Senior Data Scientist, MLOps (Spanish)
New
J
JobgetherCredit risk
Fully remote working arrangement, allowing you to work from Brazil.ContractSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Languages
- Advanced Spanish proficiency; present findings in Portuguese and Spanish.
- Experience
- At least five years of professional experience in data science, statistical modeling, or a closely related discipline.
- Required Skills
- PythonSQLMachine LearningPandasscikit-learn
Requirements
- Bachelor's degree in Statistics or a related quantitative field.
- At least five years of professional experience in data science, statistical modeling, or a closely related discipline.
- Hands-on experience in credit risk modeling, including application scoring and behavioral scoring.
- Advanced proficiency in SQL and Python for data manipulation, exploratory analysis, feature engineering, and statistical modeling.
- Practical experience developing, evaluating, and validating machine learning models, including classification, regression, and clustering.
- Familiarity with pandas, scikit-learn, statsmodels, or equivalent data science and statistical libraries.
- Advanced Spanish proficiency for communicating technical findings and collaborating with Spanish-speaking stakeholders.
- Ability to lead a workstream independently, establish priorities, and manage deliverables.
- Strong analytical thinking and critical reasoning, including the ability to challenge assumptions and identify modeling limitations.
- Strong attention to data quality, model documentation, and rigorous validation practices.
Responsibilities
- Lead the credit risk modeling workstream for the Argentinean operation and recommend modeling strategies.
- Develop application score and behavioral score models from data preparation and exploratory analysis through validation and implementation.
- Extract, transform, and analyze datasets using SQL and Python.
- Apply statistical methods and machine learning techniques, including classification, regression, and clustering.
- Select features, evaluate model assumptions, and identify variables relevant to credit risk prediction.
- Validate model performance and stability against business requirements and risk assessment standards.
- Monitor deployed models and recommend recalibration, redevelopment, or other corrective actions when performance degrades.
- Document modeling methodologies, assumptions, validation results, limitations, and recommendations.
- Present findings and model assessments to credit and risk stakeholders in Portuguese and Spanish.
- Collaborate with business, risk, and technology teams and manage the modeling workstream autonomously.
View Full Description & ApplyYou'll be redirected to the employer's site
