Cred8mo ago

data scientist

India·Hyderabadfull timemid

Data ScienceData ScientistDataData & AI

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Quick Summary

Overview

as a decision scientist, you will be the analytical backbone supporting business, growth, product, and risk teams, transforming complex data into strategic insights that drive multi-functional success across our lending ecosystem analyze multi-dimensional data to identify user patterns, emerging…

Technical Tools

pythonsqlab-testing

prefr (operated by creditvidya) is a digital-first lending platform that makes credit accessible to millions across India. With loan offerings ranging from ₹50,000 to ₹5 Lakh, we’re enabling instant personal loans and flexible pay-later credit lines, especially for first-time borrowers and underserved regions. Backed by RBI-approved NBFC partnerships, we’ve built a platform that uses selfie-based KYC, minimal documentation, and AI-powered underwriting to disburse loans within minutes.

About the Role

~3 min read

we are looking for a passionate and technically strong ai/ml engineer to join our core team driving the intelligence behind our lending platform. this is an l4-level role where you'll build high-performance ml frameworks, scale decision systems, and lay the foundation for the next evolution: agentic ai systems that autonomously extract insights, support business decisions, and power internal copilots.

if you are someone who enjoys solving hard problems at the intersection of software engineering and ml, and are excited about the future of ai agents in real-world systems, we want to hear from

design, validate, and productionize advanced machine learning and deep learning models to generate actionable insights for strategic business decisions. focus areas include credit risk prediction, propensity modeling, fraud detection, collection efficiency improvement, and other finance-related applications.

optimize and tune machine learning algorithms for performance and scalability, ensuring seamless integration with production pipelines and robustness in real-world environments.

develop and maintain monitoring frameworks to track model performance over time, detect data or concept drift, and provide timely, actionable feedback for retraining or recalibration as needed.

analyze and interpret large, complex datasets from distributed databases to generate and provide valuable actionable insights to stakeholders using big data technologies like scala-spark/pyspark.

drive continuous improvement by exploring, researching, and implementing innovative modeling techniques and algorithms.

stay up-to-date with advancements in ml/ai and proactively apply new techniques to improve model performance or uncover new opportunities.

as part of our long-term vision, contribute to building agentic systems that automate key parts of the data science pipeline from feature engineering and model selection to monitoring and reporting, enabling faster experimentation and decision-making.

have 4+ years of hands-on experience (or 2+ years if holding a master’s degree) in data science, machine learning, or analytics roles solving real-world business problems.

hold a bachelor's or master’s degree in a quantitative field such as computer science, statistics, mathematics, or a related discipline.

are proficient in programming languages like python or r, and comfortable working with large datasets and distributed computing tools.

have a strong foundation in machine learning algorithms, statistical modeling techniques, and data-driven decision-making.

excels at approaching complex problems with a structured mindset, driving data-backed and practical solutions.

communicate effectively and enjoy collaborating with cross-functional teams, including product, business, and engineering.

show strong business acumen, you don’t just build models, you build solutions that drive measurable impact.

are passionate about learning. you stay curious about new techniques, tools, and innovations in the ai space, and are excited to apply them to practical business use cases.