SRUTHI REDDY NARAPAREDDY
An avid programmer and versatile engineer with 7+ years of experience across machine learning, software development, and analytics—driven by a passion for solving complex business problems with AI. At ZS, I led the development of multi-agent LLM workflows for document automation and orchestration. Prior to that, I spent 4 years at Centific (formerly PacteraEdge) delivering AI platforms across NLP, computer vision, and predictive analytics use cases.
With a Master’s in Business Analytics from UIC, I interned at Cresco Labs to forecast product demand and quantify key drivers, and served as a data analyst building pipelines and dashboards to inform university-level decisions. I began my career at Oracle, where I developed APIs, backend services, and optimized databases for enterprise banking solutions.
Technologically agnostic and quick to ramp up on new tools, languages, and domains, I bring deep expertise in Python, SQL, Gen AI, NLP, Computer Vision, Tableau, ETL, R, A/B Testing, and statistical modeling. I'm currently seeking opportunities to lead and contribute to innovative ML/AI systems that drive measurable impact.
Personal Interests: Dance, painting, Sudoku
Education
Masters in Business Analytics, 2020
University of Illinois, Chicago
B.E in Chemical Engineering, 2016
BITS PILANI, Hyderabad
Coursework
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Data Mining
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Machine Learning
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Advanced Database Management
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Advanced Predictive Modelling
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Business Data Visualization
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Advanced Text Analytics
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Operations Management
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Revenue Management
Interests
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Data Science
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Data Visualization
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Deep Learning
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Statistics
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Generative AI / LLMs
Skills
Certifications
Projects
The Wizarding world of Harry Potter
February 2021
Deployed a flask application on cloud using AWS EBS. Go find the skills of your favorite character in Harry potter in the live application here
Python, AWS,
Flask, HTML,CSS
Customer Engagement Analysis
Spring 2020
• Built a classification model to predict customer behavior using ensemble techniques such as Random forest (RF) and XGBoost (on imbalanced data) with 98.9% recall
• Performed feature selection from 700 columns using RF and LASSO after applying SMOTE to balance the data
R, ggplot2,
SMOTE, XGBOOST,
RF, Ridge & Lasso Regression
Prediction of Net Promoter Score- Manipal Hospitals
Fall 2019
Developed Random forest and Adaboost models to predict NPS scores. Analyzed the impact of oversampling and undersampling on the prediction accuracy of both the models. Achieved higher accuracy of 74.5% with oversampled data.
R, Random forest,
Stepwise Regression,
Adaboost
Professional Experience
Sr ML Engineer
Jan 2025- Aug 2025
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Architected AI-driven solution using LangGraph to integrate multi-agent LLM workflow for decision-making and automation. Designed workflow incorporating planner, retriever, critique, and validation agents to support dynamic, context-aware task execution.
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Leading the design and development of prompt generation, authoring and data ingestion systems leveraging Textract, RAG, LangGraph, and Knowledge Graphs to improve information retrieval, task routing, and memory management. Currently leading a team of three in developing the AI module and deployment.
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Developed data ingestion, rag retrieval, and multi-agent orchestration modules.
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Designed a robust data model incorporating versioning, change tracking,