Company Overview :

Aara Tech Private Limited is a specialized technology firm focused on building advanced analytical solutions for the financial services sector.

By leveraging cutting-edge machine learning and data engineering, the company enables financial institutions to optimize their lending decisions and risk assessment frameworks.

Operating at the intersection of fintech and data science, Aara Tech provides scalable platforms that process complex alternate data to drive financial inclusion and operational efficiency.

Role Overview :

As an AI/ML Engineer specializing in Credit Risk and Alternate Data, you will be responsible for designing and deploying sophisticated predictive models that redefine how creditworthiness is assessed.

You will work closely with data scientists, risk analysts, and product teams to transform raw, unstructured data into actionable insights.

Your work will directly influence the accuracy of credit scoring engines, helping the business mitigate risk while expanding access to credit for a broader customer base.

You will be based in Chennai, contributing to a high-impact technical environment that values innovation and rigorous model validation.

Key Responsibilities :

- Develop and refine credit scoring models using advanced machine learning techniques to improve the precision of risk assessment for diverse borrower profiles.

- Engineer high-quality features from alternate data sources to capture non-traditional indicators of creditworthiness and improve model predictive power.

- Implement robust model explainability frameworks to ensure transparency and regulatory compliance in automated lending decisions.

- Build and maintain scalable APIs to integrate machine learning models into production environments, ensuring seamless communication between data pipelines and core banking systems.

- Leverage Document AI techniques to automate the extraction and analysis of financial documents, reducing manual intervention in the underwriting process.

- Collaborate with cross-functional stakeholders to translate complex business requirements into technical model specifications and performance metrics.

Required Skillset :

- Demonstrated proficiency in Python and SQL for complex data manipulation, feature engineering, and model development.

- Deep expertise in utilizing Pandas for data wrangling and XGBoost for building high-performance predictive models.

- Proven ability to design and deploy production-ready APIs that support real-time decisioning systems.

- Strong understanding of model explainability techniques, ensuring that complex algorithms remain interpretable for risk management and audit purposes.

- Experience in applying Document AI to extract insights from unstructured financial data, enhancing the efficiency of credit workflows.

- Excellent communication skills with the ability to articulate technical findings to non-technical stakeholders and work effectively within a collaborative team environment.

- A minimum of 4 to 7 years of professional experience in a quantitative or machine learning role, ideally within the fintech or banking domain.

- A degree in Computer Science, Statistics, Mathematics, or a related quantitative field from a reputed institution.