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Data scientist specializing in NLP and GenAI pipelines, with hands-on experience building LLM-based knowledge models, evaluation frameworks, and automated workflows. Skilled in hybrid ML routing, quality gates, and scalable data pipelines across cloud environments. Experienced in developing anomaly detection, churn modeling, and drift-triggered MLOps pipelines. Strong foundation in machine learning, deep learning, and engineering best practices using Python, SQL, PyTorch/TensorFlow, and modern orchestration tools.…Data scientist specializing in NLP and GenAI pipelines, with hands-on experience building LLM-based knowledge models, evaluation frameworks, and automated workflows. Skilled in hybrid ML routing, quality gates, and scalable data pipelines across cloud environments. Experienced in developing anomaly detection, churn modeling, and drift-triggered MLOps pipelines. Strong foundation in machine learning, deep learning, and engineering best practices using Python, SQL, PyTorch/TensorFlow, and modern orchestration tools.

KARTIK RAUT

Data Scientist, AI Engineer, Programmer, +3

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Data scientist specializing in NLP and GenAI pipelines, with hands-on experience building LLM-based knowledge models, evaluation frameworks, and automated workflows. Skilled in hybrid ML routing, quality gates, and scalable data pipelines across cloud environments. Experienced in developing anomaly detection, churn modeling, and drift-triggered MLOps pipelines. Strong foundation in machine learning, deep learning, and engineering best practices using Python, SQL, PyTorch/TensorFlow, and modern orchestration tools.…Data scientist specializing in NLP and GenAI pipelines, with hands-on experience building LLM-based knowledge models, evaluation frameworks, and automated workflows. Skilled in hybrid ML routing, quality gates, and scalable data pipelines across cloud environments. Experienced in developing anomaly detection, churn modeling, and drift-triggered MLOps pipelines. Strong foundation in machine learning, deep learning, and engineering best practices using Python, SQL, PyTorch/TensorFlow, and modern orchestration tools.

Available to hire

Data scientist specializing in NLP and GenAI pipelines, with hands-on experience building LLM-based knowledge models, evaluation frameworks, and automated workflows. Skilled in hybrid ML routing, quality gates, and scalable data pipelines across cloud environments.

Experienced in developing anomaly detection, churn modeling, and drift-triggered MLOps pipelines. Strong foundation in machine learning, deep learning, and engineering best practices using Python, SQL, PyTorch/TensorFlow, and modern orchestration tools.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Intermediate

Hindi

Advanced

Work Experience

Data Scientist at METY Technology

July 1, 2025 - Present

Engineered an end-to-end GenAI pipeline using GPT-4 and prompt engineering to automate knowledge model generation across 112 topics with ~90% SymPy-verified accuracy. Built NLP workflows using LLM-based classification and JSON extraction to generate structured 11-field knowledge models, eliminating manual authoring. Architected a hybrid ML routing system with four-strategy fallback logic across 15+ handlers, achieving zero unhandled topic failures with graceful degradation. Defined evaluation metrics across a five-layer quality framework using PRM-style multidimensional scoring and confidence thresholds to enforce structured quality gates (~90% pass rate). Automated a multi-stage pipeline from Excel ingestion through LLM transformation and validation to significantly reduce template creation time while maintaining ~90% output accuracy per stakeholder feedback.

Data Scientist at Accenture

December 1, 2020 - June 30, 2023

Built anomaly detection using a three-layer approach (Isolation Forest, Autoencoders, Bayesian changepoint) with root-cause analysis, reducing false alarms by 38%. Developed a churn model using CatBoost with Focal Loss, achieving 82% precision and 75% recall; reduced churn by 12% via A/B testing. Deployed 4G/5G monitoring with Bayesian changepoint detection using Grafana and InfluxDB, detecting degradations 27% earlier. Architected a drift-triggered MLOps pipeline with Evidently AI triggering Jenkins for MLflow retraining, cutting validation time by 35%. Built customer segmentation (K-means, DBSCAN) for telecom marketing campaigns, increasing campaign ROI by 28%.