Cientista de Dados Sênior
New
J
JobgetherFinancial Analytics
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLMachine LearningMLOps
Requirements
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related technology, quantitative, or exact-sciences field.
- Professional experience developing statistical models and applying data science techniques to complex business problems.
- Strong knowledge of statistics, exploratory data analysis, predictive modeling, and machine learning.
- Solid Python skills for developing analytical and predictive models.
- Experience with SQL and the ability to work effectively with structured and corporate datasets.
- Knowledge of model performance monitoring, validation, and analytical quality practices.
- Familiarity with agile methodologies and collaborative delivery environments.
- Knowledge of AWS, particularly SageMaker, or GCP, particularly Vertex AI, is desirable.
- Strong analytical and problem-solving abilities, with the capacity to translate complex datasets into clear business insights.
- Strong communication skills and the ability to present technical findings and recommendations to both technical and non-technical stakeholders.
- A continuous-learning mindset and interest in applying data science to evolving financial and business challenges.
- Knowledge of credit-risk concepts, particularly IFRS 9, is a strong advantage.
- Experience applying data science to financial problems and familiarity with MLOps environments are considered valuable differentiators.
Responsibilities
- Develop and continuously improve statistical and predictive models for key credit-risk indicators, including delinquency, provision expenses, and credit losses.
- Analyze corporate databases and business processes to identify factors that influence credit risk and support more comprehensive risk assessments.
- Enhance statistical modeling methodologies for Expected Credit Loss, incorporating forward-looking analyses to improve the accuracy of credit-risk measurement.
- Perform exploratory data analysis and develop ad hoc models and analyses to address financial-risk challenges across different business areas.
- Conduct model versioning, backtesting, performance monitoring, and continuous validation to ensure the reliability and effectiveness of analytical solutions.
- Prepare reports, analyses, insights, and recommendations for senior leadership and business teams to support strategic decision-making and credit-risk management.
- Maintain and update methodological documentation, procedures, and policies, incorporating changes to existing activities and introducing new analytical processes when required.
- Partner with business and technology stakeholders to understand requirements, translate complex problems into analytical solutions, and communicate findings clearly.
- Contribute to the adoption of agile methodologies and modern data-science practices across risk and financial analytics initiatives.
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