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data scientist

CRED

Hyderabad, Telangana, IndiaJobNo compensation foundPosted 8mo agoVerified open today

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At a glance

Compensation
No compensation found
Location
Hyderabad, Telangana, India
Work Authorization
Not specified

Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

Prefr, a digital‑first lending platform, seeks a passionate AI/ML engineer to build high‑performance machine‑learning frameworks, scale decision systems, and develop agentic AI solutions that drive credit risk prediction, fraud detection and other finance‑related insights across India.

Skills & qualifications

RequiredNice to have

Skills

PythonAnalyticsUnderwritingArtificial IntelligenceMachine LearningDistributed SystemsActionable InsightsStatisticsStrategic PartnershipsRScala‑SparkPySparkDeep LearningStatistical ModelingData ScienceDistributed ComputingBig DataAIAgentic AICommunicationBusiness AcumenStructured Problem Solving

Qualifications

Bachelor's or Master's Degree in Quantitative Field4+ Years Experience

Full job description

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

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

what you will do :

  • 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.

you should apply if :

  • 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.

You've read the whole posting — now see how you match it.