Role Overview
We are seeking a Data Science Intern for a four-month internship to support the development of our credit analytics, portfolio monitoring, and underwriting capabilities.
The intern will work with loan-level, repayment, and collateral datasets, build analytical dashboards, and assist in developing automated underwriting and risk assessment tools using Python and AWS.
This role offers hands-on exposure to private credit, fintech lending, data engineering, credit risk analytics, business intelligence, and cloud-based application development. Based on performance and mutual agreement the role offers a pathway to a full-time position by the end of the internship.
Key Responsibilities
- Use Python and pandas to clean, validate, reconcile, and transform large loan-level, repayment, collateral, and portfolio datasets.
- Develop repeatable data-processing pipelines for borrower, loan, repayment, delinquency, and collateral information received from portfolio companies.
- Perform data quality checks and investigate discrepancies across loan tapes, repayment schedules, financial records, and collateral reports.
- Calculate portfolio and credit risk metrics, including outstanding principal, delinquency buckets, vintage performance, repayment rates, concentration levels, collateral coverage, and weighted-average portfolio characteristics.
- Design, develop, and maintain interactive portfolio monitoring and risk dashboards using Amazon QuickSight.
- Prepare datasets, calculated fields, and visualisations for portfolio analysis, trend monitoring, and management reporting.
- Assist in developing underwriting algorithms, credit assessment models, and automated decision-making tools using Python.
- Deploy and maintain underwriting calculations, data-validation processes, and scoring logic using AWS Lambda and other AWS services.
- Support the integration of underwriting models with internal platforms, databases, and application programming interfaces.
- Test, document, and improve existing analytical models, data pipelines, dashboards, and automation workflows.
- Work closely with the investment, credit, portfolio monitoring, and technology teams to translate business and underwriting requirements into analytical solutions.
- Assist with ad hoc data analysis, portfolio reviews, operational projects, and technology-related initiatives as required.
Qualificationsand Skills
- Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Finance, or a related discipline.
- Strong working knowledge of Python, particularly pandas, NumPy, and data-processing workflows.
- Familiarity with SQL and relational or document-based databases.
- Understanding of data cleaning, data validation, exploratory data analysis, and statistical modelling.
- Strong analytical and problem-solving skills, with close attention to data accuracy and detail.
- Ability to work with complex, incomplete, and inconsistently structured datasets.
- Clear written and verbal communication skills.
- Ability to work independently while collaborating effectively across business and technical teams.
PreferredExperience
- Experience with Amazon Web Services, particularly AWS Lambda, Amazon S3, Amazon QuickSight, and related data services.
- Experience building dashboards or business intelligence reports.
- Familiarity with machine learning, credit scoring, financial modelling, or risk analytics.
- Knowledge of lending, fintech, private credit, loan servicing, or collateral monitoring.
