AI/ML Engineer with 4+ years of experience building machine learning, NLP, LLM, Retrieval-Augmented Generation, and predictive analytics solutions for enterprise intelligence, business analytics, and decision-support use cases. Skilled in Python, SQL, PySpark, Azure Databricks, AWS, scikit-learn, MLflow, and MLOps practices, delivering scalable data workflows, model pipelines, and production-ready integrations. Experienced in experimentation, model validation, monitoring, CI/CD-aware MLOps, and creating recommendation systems, segmentation models, and forecasting solutions. Proficient in feature engineering, API-ready model integration, and translating complex datasets into actionable stakeholder recommendations across agile delivery environments.

Manaswini Beereddy

AI/ML Engineer with 4+ years of experience building machine learning, NLP, LLM, Retrieval-Augmented Generation, and predictive analytics solutions for enterprise intelligence, business analytics, and decision-support use cases. Skilled in Python, SQL, PySpark, Azure Databricks, AWS, scikit-learn, MLflow, and MLOps practices, delivering scalable data workflows, model pipelines, and production-ready integrations. Experienced in experimentation, model validation, monitoring, CI/CD-aware MLOps, and creating recommendation systems, segmentation models, and forecasting solutions. Proficient in feature engineering, API-ready model integration, and translating complex datasets into actionable stakeholder recommendations across agile delivery environments.

Available to hire

AI/ML Engineer with 4+ years of experience building machine learning, NLP, LLM, Retrieval-Augmented Generation, and predictive analytics solutions for enterprise intelligence, business analytics, and decision-support use cases. Skilled in Python, SQL, PySpark, Azure Databricks, AWS, scikit-learn, MLflow, and MLOps practices, delivering scalable data workflows, model pipelines, and production-ready integrations.

Experienced in experimentation, model validation, monitoring, CI/CD-aware MLOps, and creating recommendation systems, segmentation models, and forecasting solutions. Proficient in feature engineering, API-ready model integration, and translating complex datasets into actionable stakeholder recommendations across agile delivery environments.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Beginner
Beginner
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Work Experience

AI/ML Engineer at Gartner - Stamford, CT
January 1, 2025 - Present
Designed machine learning models to analyze 250K+ client engagement records across advisory usage, research consumption, and business priority signals to surface trends, risks, and decision opportunities. Built scalable data preparation workflows in Azure Databricks using Python and PySpark to clean, transform, and engineer features from CRM, survey, research, and client interaction data sources. Developed SQL extraction, validation, and reconciliation processes for client/advisory/research datasets to reduce inconsistencies and improve reliability for reporting and model training. Created NLP pipelines to analyze advisory notes, survey feedback, research content, and client interactions by extracting business themes, sentiment patterns, and emerging technology topics. Implemented LLM and Retrieval-Augmented Generation workflows using embeddings, semantic search, LangChain concepts, and vector database approaches to generate grounded AI recommendations using enterprise knowledge sourc
Data Scientist - Analytics & ML at Coi mbatore, India
December 1, 2020 - October 1, 2023
Analyzed enterprise datasets across QSR, retail, healthcare, and manufacturing domains to identify customer behavior trends, demand patterns, operational gaps, and business-performance drivers. Extracted and validated structured data using SQL from business systems and AWS-based sources to improve data accuracy for predictive analytics, KPI reporting, and machine learning use cases. Cleaned, transformed, and standardized large datasets using Python, Pandas, and NumPy by handling missing values, duplicates, outliers, and inconsistent records, including discrepancy reporting. Performed exploratory, statistical, correlation, and trend analysis to uncover insights supporting forecasting, segmentation, performance optimization, and business planning. Engineered features from customer, sales, transaction, and operational data to support demand forecasting, churn analysis, customer segmentation, and sales trend prediction models. Developed scikit-learn models for regression, classification,

Education

Master of Science in Computer Science at Sacred Heart University
January 1, 2024 - March 1, 2025
Bachelor of Technology in Computer Science and Engineering at Karu nya Institute of Technology and Sciences
July 1, 2019 - May 1, 2023

Qualifications

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Industry Experience

Professional Services, Software & Internet, Financial Services