Silverstreak Analytics Hiring! Full Time Intern, Data Science, Risk Management in - Ricebowl

Company Description

Silverstreak Analytics is an AI-enabled credit investment platform in its early growth phase. We support institutional investors in researching, benchmarking, structuring, and monitoring credit transactions involving new-economy technology businesses across Emerging Asia, including fintech lenders, SaaS companies, mobility platforms, and e-commerce ecosystems.

As we continue to grow, we are seeking high-calibre individuals with strong analytical capabilities and an interest in financial markets, technology, and cross-border credit investing. The internship offers exposure to institutional credit underwriting, portfolio analytics, and technology-driven investment solutions across the region.

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.

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;

Qualifications and 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.

Preferred Experience

• 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.

Compensation: from SGD 2,000 to 2,500 per month;

Setting: Onsite, Full-time;

Duration: 4 Months from August 2026; can be extended upon mutual agreement.