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.

What we expect you to do:
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 / current-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 workplace
Translate complex analytical outputs into explicit business recommendations for
stakeholders

Requirements
What you bring to the table:
2–5 years of experience in credit risk analytics, lending analytics, or fintech data
science.
Master’s degree in a quantitative field such as Statistics, Computer Science,
Economics, Applied Mathematics, or related discipline.
Hands-on experience in statistical modeling, machine learning, and predictive
analytics.
Strong ability to work with messy, real-world datasets (incomplete, noisy, biased)
and large-scale data processing.
Experience in small business lending, fintech, or alternative credit ecosystems.
Familiarity with model governance, validation frameworks, and explainability
techniques (

📌 Data Scientist Hyderabad
🏢 TekFriday Processing Solutions
📍 Hyderabad