Data Scientist

Role & responsibilities :

- Develop and maintain credit risk models using bureau data (e.g., credit scores, attributes, trended data)

- Design and implement attribute engineering strategies using raw bureau data

- Analyze bureau data patterns to identify new risk indicators and opportunities

- Conduct regular model performance monitoring and validation

- Partner with business teams to translate analytical insights into actionable lending strategies

- Evaluate and recommend optimal bureau data packages and attributes for different products

- Build bureau data quality monitoring frameworks

- Create and maintain bureau data documentation and data dictionaries

Preferred candidate profile :

- Master's degree in Statistics, Mathematics, Computer Science, or related field

- 5+ years of experience working with banking & Finance (BFSI)

- Strong understanding of credit risk concepts and regulatory requirements

- Expertise in statistical modeling techniques (logistic regression, survival analysis, machine learning etc)

- Proficiency in SQL, Python/R, and data visualization tools

- Knowledge of credit reporting regulations and compliance requirements

Technical Skills:

- Advanced SQL querying and optimization

- Python/R packages for data manipulation and modeling

- Big data technologies (Hadoop, Spark)

Soft Skills:

- Strong analytical and problem-solving abilities

- Excellent communication skills to explain complex concepts to non-technical stakeholders

- Project management and organizational skills

- Ability to work independently and as part of a team

- Detail-oriented with strong documentation habits

Impact & Deliverables:

- Develop credit risk models that improve portfolio performance

- Create automated reporting systems for bureau data monitoring

- Design attribute strategies that optimize bureau data usage

- Provide analytical support for credit policy decisions

- Generate insights to improve customer acquisition and risk assessment