Data Scientist – Voice AI

About Credgenics

Credgenics is India's leading SaaS-based debt collection platform, helping banks, NBFCs, FinTechs, and ARCs digitize and automate their collection processes. By leveraging AI, ML, and advanced analytics, we enable financial institutions to improve recovery rates, optimize collection spends, and enhance operational efficiency.

At Credgenics, we thrive in a culture of innovation and agility—exploring new technologies, solving complex challenges, and maintaining consistency in an ever-changing financial landscape. If you’re passionate about Voice AI, GenAI, and conversational automation, apply today!

Role Overview

As a Data Scientist – Voice AI, you will be responsible for developing and deploying GenAI-powered STT and TTS models that drive voicebot automation within our collections platform. You’ll collaborate with cross-functional teams to implement real-world voice solutions that improve customer interactions, reduce manual intervention, and scale conversational engagement.

What You’ll Be Doing

• Voicebot Model Deployment – Implement and fine-tune STT and TTS models for real-time customer conversations.
• Conversational AI Integration – Work with engineering teams to embed speech models into collection workflows and customer engagement platforms.
• Scalable AI Solutions – Develop production-ready ML pipelines for speech models, ensuring low latency and high accuracy.
• Performance Monitoring – Continuously track and optimize model performance (accuracy, latency, naturalness of voice).
• Workflow Automation – Enable automation of customer communication through seamless voicebot deployment.
• Cross-Team Collaboration – Partner with product managers, engineers, and operations teams to design applied AI solutions for debt lifecycle management.

What We’re Looking For

• 4+ years of experience in Voice AI, Voicebot development, or Conversational AI, preferably in a product/startup environment.
• Strong experience with speech recognition (STT/ASR) and speech synthesis (TTS) deployment.
• Hands-on experience with ML/DL frameworks (PyTorch, TensorFlow, Keras).
• Good programming skills in Python and experience in API-based model integration.
• Practical experience deploying models in production environments (on cloud – AWS, GCP, Azure).
• Experience working on latency optimization, error reduction, and real-time deployment of speech models.
• Ability to collaborate across teams and deliver impactful, applied AI solutions.