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    Intern, Data Science, Risk Management

    Silverstreak Analytics

    Singapore, SingaporeInternship24 Jul 2026

    About this internship

    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.