About Credgenics:

Credgenics is the leading full-stack, AI-powered loan collections and debt resolution technology platform for Banks, Non-Banking Financial Companies (NBFCs), FinTechs, and Asset Reconstruction Companies (ARCs) globally. Recognised as the Best Selling Loan Collections Platform in India by IBS Intelligence in their Annual India Sales League Table for three consecutive years, Credgenics is modernizing debt recovery processes. The platform combines predictive and generative AI capabilities to assess risk, segment borrowers, and execute personalized recovery strategies across the end-to-end collections lifecycle. Supporting all credit products across retail and

SME/MSME portfolios, Credgenics empowers lenders to accelerate recoveries, optimize operational efficiency, and scale smarter, data-driven collections. In FY24, the platform managed over 98 million loan accounts worth more than USD 250 billion and facilitated over 1.7 billion omnichannel communications, serving 150+ financial institutions worldwide.

Role Overview

We are looking for a Data Scientist with experience in NLP and Machine Learning to work on Conversational AI solutions including chatbots, voice assistants, and AI-driven automation systems. The role involves working with LLMs, ASR, NLP models, and classical ML techniques to build and improve intelligent conversational systems.

Key Responsibilities

• Develop and improve NLP and Conversational AI models for chatbot and voice bot applications.
• Work with Large Language Models (LLMs) for prompt engineering, evaluation, and experimentation.
• Support development of speech recognition (ASR) and speech understanding pipelines.
• Build machine learning models using classical ML techniques (Logistic Regression, Random Forest, Gradient Boosting, etc.).
• Perform data preprocessing, feature engineering, and exploratory data analysis.
• Evaluate model performance and collaborate with engineering teams for model deployment.

Required Skills

• 2–4 years of experience in Data Science / Machine Learning / NLP.
• Strong programming skills in Python.
• Experience with ML libraries such as Scikit-learn, PyTorch, or TensorFlow.
• Knowledge of NLP concepts and transformer/LLM models.
• Familiarity with speech technologies or ASR is a plus.