Data Scientist

TekFriday Processing Solutions Pvt Ltd; Hyderabad; On-site; INR 900,000 - 1,500,000; Full time

Job summary

TekFriday Processing Solutions Pvt Ltd in Hyderabad is seeking a data-driven Credit Risk Data Scientist to join our fintech team. You will design and deploy intelligent credit decisioning systems that directly influence business outcomes.

You will work at the intersection of risk, product, and growth, building models, data pipelines, and APIs that enable real-time underwriting decisions across large-scale, imbalanced datasets.

Responsibilities

• Build, validate, and deploy real-time credit risk and fraud detection models to support underwriting decisions
• Work with large-scale, imbalanced datasets to extract meaningful risk insights
• Develop thin-file / new-to-credit models using alternative data sources (mobile, transactional, behavioural signals)
• Optimize credit underwriting strategies including approval rates, credit limits, and pricing decisions
• Design and execute A/B experiments to improve portfolio performance while maintaining risk thresholds
• Continuously monitor model performance, stability, and drift; recommend recalibration strategies
• Collaborate with Product, Engineering, and Growth teams to integrate models into scalable APIs and decision systems
• Build and maintain automated data pipelines and model retraining workflows
• Balance risk vs. growth trade-offs, aligning with business objectives in a fintech lending environment
• Translate complex analytical outputs into clear business recommendations for stakeholders

Job description

We are looking for a data-driven and impact-oriented Credit Risk Data Scientist to join our high-performance fintech team. This role sits at the intersection of risk, product, and growth, where you will design and deploy intelligent credit decisioning systems that directly influence business outcomes.

Responsibilities

• Build, validate, and deploy real-time credit risk and fraud detection models to support underwriting decisions
• Work with large-scale, imbalanced datasets to extract meaningful risk insights
• Develop thin-file / new-to-credit models using alternative data sources (mobile, transactional, behavioural signals)
• Optimize credit underwriting strategies including approval rates, credit limits, and pricing decisions
• Design and execute A/B experiments to improve portfolio performance while maintaining risk thresholds
• Continuously monitor model performance, stability, and drift; recommend recalibration strategies
• Collaborate with Product, Engineering, and Growth teams to integrate models into scalable APIs and decision systems
• Build and maintain automated data pipelines and model retraining workflows
• Balance risk vs. growth trade-offs, aligning with business objectives in a fintech lending environment
• Translate complex analytical outputs into clear business recommendations for stakeholders