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Hi, I’m Hari Shankar Raghuraman, a Senior Data Scientist/AI-ML Engineer with 5+ years of experience building and deploying machine learning, statistical modeling, and predictive analytics solutions across large-scale cloud and big data environments. I specialize in forecasting, customer analytics, anomaly detection, NLP, experimentation, and optimization, using Python, SQL, Spark, TensorFlow, and PyTorch. I enjoy turning complex business problems into scalable data-driven solutions that improve model performance, operational efficiency, and decision-making. In roles at Cisco Systems and Accenture, I’ve designed end-to-end ML pipelines, deployed production-grade models on AWS, and collaborated with cross-functional teams to translate requirements into measurable business impact. I thrive in cross-functional environments and continuously learn to stay ahead in ML/AI.…Hi, I’m Hari Shankar Raghuraman, a Senior Data Scientist/AI-ML Engineer with 5+ years of experience building and deploying machine learning, statistical modeling, and predictive analytics solutions across large-scale cloud and big data environments. I specialize in forecasting, customer analytics, anomaly detection, NLP, experimentation, and optimization, using Python, SQL, Spark, TensorFlow, and PyTorch. I enjoy turning complex business problems into scalable data-driven solutions that improve model performance, operational efficiency, and decision-making. In roles at Cisco Systems and Accenture, I’ve designed end-to-end ML pipelines, deployed production-grade models on AWS, and collaborated with cross-functional teams to translate requirements into measurable business impact. I thrive in cross-functional environments and continuously learn to stay ahead in ML/AI.

Hari Shankar Raghuraman

Data Scientist, AI Engineer, AI Developer, +2

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Hi, I’m Hari Shankar Raghuraman, a Senior Data Scientist/AI-ML Engineer with 5+ years of experience building and deploying machine learning, statistical modeling, and predictive analytics solutions across large-scale cloud and big data environments. I specialize in forecasting, customer analytics, anomaly detection, NLP, experimentation, and optimization, using Python, SQL, Spark, TensorFlow, and PyTorch. I enjoy turning complex business problems into scalable data-driven solutions that improve model performance, operational efficiency, and decision-making. In roles at Cisco Systems and Accenture, I’ve designed end-to-end ML pipelines, deployed production-grade models on AWS, and collaborated with cross-functional teams to translate requirements into measurable business impact. I thrive in cross-functional environments and continuously learn to stay ahead in ML/AI.…Hi, I’m Hari Shankar Raghuraman, a Senior Data Scientist/AI-ML Engineer with 5+ years of experience building and deploying machine learning, statistical modeling, and predictive analytics solutions across large-scale cloud and big data environments. I specialize in forecasting, customer analytics, anomaly detection, NLP, experimentation, and optimization, using Python, SQL, Spark, TensorFlow, and PyTorch. I enjoy turning complex business problems into scalable data-driven solutions that improve model performance, operational efficiency, and decision-making. In roles at Cisco Systems and Accenture, I’ve designed end-to-end ML pipelines, deployed production-grade models on AWS, and collaborated with cross-functional teams to translate requirements into measurable business impact. I thrive in cross-functional environments and continuously learn to stay ahead in ML/AI.

Available to hire

Hi, I’m Hari Shankar Raghuraman, a Senior Data Scientist/AI-ML Engineer with 5+ years of experience building and deploying machine learning, statistical modeling, and predictive analytics solutions across large-scale cloud and big data environments. I specialize in forecasting, customer analytics, anomaly detection, NLP, experimentation, and optimization, using Python, SQL, Spark, TensorFlow, and PyTorch. I enjoy turning complex business problems into scalable data-driven solutions that improve model performance, operational efficiency, and decision-making.

In roles at Cisco Systems and Accenture, I’ve designed end-to-end ML pipelines, deployed production-grade models on AWS, and collaborated with cross-functional teams to translate requirements into measurable business impact. I thrive in cross-functional environments and continuously learn to stay ahead in ML/AI.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Cisco Systems

February 1, 2024 - Present

Designed and deployed scalable ML pipelines processing 50+ TB of structured and unstructured data using Python, PySpark, and Apache Spark, boosting data processing efficiency by 40% and accelerating model training cycles. Built predictive models with Scikit-learn, XGBoost, and TensorFlow for customer behavior analysis and anomaly detection, increasing accuracy by 28% and reducing false positives by 22%. Developed end-to-end deep learning models with PyTorch and Transformer architectures for NLP tasks (sentiment analysis and text classification), improving classification performance by ~30%. Implemented MLOps pipelines with MLflow, Docker, and Kubernetes to automate training, versioning, and deployment, reducing deployment time by 45% and enabling scalable production. Integrated models into RESTful APIs via FastAPI and deployed on AWS SageMaker and EC2 for real-time inference with latency reduced by 35%. Engineered robust ETL pipelines with Apache Airflow and dbt to automate ingestion,

Machine Learning Engineer at Accenture

July 1, 2019 - July 1, 2022

Developed and implemented machine learning models using Python, Scikit-learn, and TensorFlow for predictive analytics and classification tasks, improving forecasting accuracy by 26% across multiple client projects. Processed and analyzed large-scale datasets using SQL, Pandas, and PySpark, handling over 30 TB of data and optimizing data pipelines to reduce processing time by 35%. Built data preprocessing and feature engineering pipelines to clean, transform, and standardize raw data, improving data quality and model performance by 22%. Designed and implemented ETL workflows using Apache Airflow and SQL-based pipelines, ensuring reliable data integration and improving pipeline efficiency by 30%. Developed NLP-based solutions using NLTK and Transformer-based models for text classification and sentiment analysis, enhancing customer insights and improving analysis accuracy by 27%. Deployed ML models using Docker containers and cloud services such as AWS EC2 and S3, ensuring scalable and re