Hello!

I'm Vaishnavi Nanduri



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Name: Vaishnavi Nanduri

Education: M.S in Data Science San Jose State University(SJSU)

Previous Work Experience: 4 Years 7 Months

Address: San Jose

About

About Me

I am a data science professional with a robust foundation in computer science, currently pursuing a Master’s in Data Analytics at San Jose State University. With over four years of industry experience, I have consistently delivered impactful solutions — from creating dynamic visualizations to engineering scalable data systems. My journey has been marked by roles of increasing responsibility, including leading teams, optimizing processes, and leveraging cutting-edge tools to solve complex challenges.

Previously at Microsoft via Accenture, I spearheaded the development of 50+ Power BI reports and predictive models, enhancing decision-making efficiency and operational effectiveness across departments.

My academic projects are where real-world chaos meets technical curiosity — and sparks fly. I’ve analyzed large-scale crash data to uncover patterns in public safety, built real-time energy forecasting systems using distributed streaming architectures, and developed personality-aware emotion generation models using neural networks. I’ve also designed a mock interview platform that leverages large language models and real-time speech analysis, simulated Uber-inspired systems for ride-sharing and food delivery, and engineered malware detection pipelines that combine traditional machine learning with generative AI for explainable threat reasoning.

✨ Always learning and ready for the next data challenge!

Resume

Resume

Seasoned Senior Data Analyst with 4+ years of experience driving business strategies,backend development, building data pipelines, and data analysis. Proficient in the latest AI/ML technologies, with a proven ability to drive business outcomes through data insights.

Experience


Aug'25 – Dec'25

Graduate Teaching Assistant (Part time)

San Jose State University

San Jose, CA

  • Big Data Technologies : Provided instructional support to 40 graduate students in distributed data processing, streaming frameworks, and real-time analytics. Assisted with Spark, Kafka, MapReduce, Bloom Filters, Flajolet-Martin, LSH, differential privacy, and federated learning. Guided students through assignments and scalable project implementations.
  • Database Management Systems : Supported SQL programming, ER modeling, schema design, normalization, views, triggers, and JDBC. Helped 130 undergraduate students with MySQL setup, debugging queries, and understanding relational database concepts through office hours and project reviews.
  • Contributed to grading, exam review sessions, and technical mentoring to enhance student learning and project outcomes.

June'25 - Aug'25

Data Science Intern

Netgear

San Jose, CA

  • Replaced manual Excel-based workflows with optimized Oracle SQL scripts, reducing reporting time by 60%. Built a structured GitHub repository to improve version control, reuse, and cross-team collaboration.
  • Analyzed Walmart’s OTIF (On-Time In-Full) shipment data to identify patterns in early, late, and unfulfilled deliveries. Extended it by developing a machine learning model that forecasted penalty risks for upcoming weeks with 71% accuracy. Delivered insights through dynamic Power BI dashboards for use in weekly reviews.
  • Investigated supplier quality chargebacks by analyzing barcode and label compliance data under Walmart’s SQEP (Supplier Quality Excellence Program) guidelines. Designed actionable dashboards that visualized root causes by SKU and vendor, contributing to a 40% reduction in chargebacks.
  • Developed a sourcing cost model using Python and Excel to support rework operations (CTO, RWO, MRB), improving procurement decisions by visualizing lead times, cost structures, and trade-offs across internal, local, and inter-DC supply channels.

Jan'22– Dec'23

Senior Data Analyst

Microsoft via Accenture

Hyderabad, India

  • Spearheaded the creation and enhancement of 50+ Power BI reports and 100+ visualizations, boosting data accessibility for 10+ departments and increasing operational efficiency by 20%.
  • Crafted predictive models and actionable insights using Python, improving decision-making efficiency by 25% and reducing reporting errors by 15%.
  • Utilized SQL Server and Azure Synapse Analytics to optimize data pipelines, reducing downtime by 5 hours/month and increasing data consistency by 25%.
  • Orchestrated complex data transformations using DAX/MDAX, improving KPI accuracy for 10,000+ employees by 15%.
  • Developed robust data models leveraging Azure Synapse and SQL databases, resulting in a 25% improvement in data quality and reporting efficiency.
  • Led a team of 16, implementing a POD model that increased team efficiency by 30%, reduced incidents by 20+/month, and improved SLA adherence by 25%.

June'21– Dec'21

Data Analyst

Microsoft via Accenture

Hyderabad, India

  • Formulated Power BI metrics for payroll, revenue, and utilization, optimizing KPI tracking for 2,000+ employees and saving 10 hours/week in report preparation.
  • Generated 100+ Power BI visualizations, enhancing data accuracy by 20% and improving interpretation of key metrics.
  • Resolved 15+ technical issues monthly, reducing report generation errors by 25% and boosting data reliability by 10%.

June'19– June'21

Associate Data Analyst

Microsoft via Accenture

Hyderabad, India

  • Imported and transformed data from SQL Server and Azure SQL, producing 20+ Power BI reports that increased data accessibility by 30% across multiple departments.
  • Utilized Power BI measures and visualizations, elevating business KPIs by 15%.

May'18 - June'18

Software Engineer Intern

Tech Mahindra

Hyderabad, India

  • Contributed to SAP SuccessFactors Human Capital Management (HCM) solutions by enhancing data integration and system processes.
  • Engineered dynamic web pages using JSF, automating backend data retrieval from 10+ seconds to under 5 seconds, boosting system performance by 50%.



Education


2015-2019

Bachelor of Technology in Computer Science and Engineering

GITAM University, Visakhapatnam, India
2024-2025

Master of Science in Applied Data Science

San Jose State University, San Jose

Projects

Projects

AI-Driven Mock Interview System with Real-Time Feedback and Dialogue Flow

✓ Approved & Used by SJSU for MS Applied Data Science Mock Interview Curriculum

Built an end-to-end AI mock interview platform enabling company-specific, role-aware, multi-turn interviews powered by fine-tuned LLaMA-3, Mistral-7B, Gemma-7B, and Qwen2.5-3B models. Integrated RAG (Pinecone + SBERT), Gemini NER, and Whisper for voice-based Q&A. Achieved 2× more specific feedback vs. baseline and <1.12s response latency using Qwen2.5-3B (PPL 4.64, LLM-Judge 3.9 of 5). Full-stack deployment via React, FastAPI, MongoDB Atlas, BigQuery, and Cloud Run with analytics dashboards.

Ex-PErt: Explainable PE Malware Detection

Developed a hybrid LightGBM + LLM reasoning pipeline using RAG to classify PE malware with high interpretability. Achieved F1 = 0.916, Recall = 0.917, and ROC-AUC ≈ 0.976. Produced human-readable threat explanations, reducing false negatives by ~20% over ML-only baselines.

Personality-Affected Emotion Generation in Dialog Systems

Engineered a personality-aware emotion prediction model using BERT/DeBERTa embeddings, BiGRU context modeling, and GNN fusion with OCEAN traits + VAD signals. Achieved +6 macro-F1 over transformer baselines and mood regression MSE = 0.053.

Uber Transport Simulation

Designed a Kafka-based distributed system with SQL caching and ML models for scalable fare estimation and dynamic pricing.

Machine Learning Driver Anomaly Detection for ICS with IEC 60870-5-104

Built an ML-based anomaly detection system with Random Forest, KNN, XGBoost, and Streamlit dashboard for real-time results.

Uber Eats Simulation

Developed a containerized platform using Django, React, Kubernetes, and AWS with secure auth, order tracking, and MongoDB integration.

Weather and Solar Energy: Prediction and Analysis

Real-time energy prediction with Apache Kafka, Spark, Cassandra, and RF. Added privacy with LSH, K-anonymity, and machine unlearning.

Airline Data Odyssey: From Collection to Analysis

Processed over 50,000 records with BigQuery and visualized flight delay patterns using Neo4j, Seaborn, and Matplotlib.

Charting the route to safety: Visualizing Chicago's Road Crash Data

Analyzed 155K crash records and built interactive dashboards to showcase accident trends, damages, and fatalities.

Contact

Contact Me

Below are the details to reach out to me!

Address

San Jose, CA

Email Address

vaishunan4@gmail.com

vaishnavi.nanduri@sjsu.edu

LinkedIn

My LinkedIn