Praneeth
Varma
A decade of turning ambiguous data into product strategy and measurable business impact at the world's most influential tech companies.
Numbers That Tell the Story
The Person Behind the Data
I've spent the last decade at the intersection of data and product — turning ambiguity into clarity at companies that serve billions of people.
It started at Google, where I hunted fraud patterns across Shopping that saved millions in losses. At Amazon, I partnered with ML scientists to tune search algorithms across the US and India. At Microsoft, I powered 25+ global campaigns for Azure and Office, then rebuilt analytics pipelines from the ground up. Now at Intuit, I'm building the fraud intelligence frameworks that protect customers at scale.
I don't just analyze data — I translate it into strategy. Whether it's defining the KPIs that matter, designing experiments that actually answer the question, or building dashboards that drive decisions, I care about one thing: impact.
Outside of work, I'm experimenting with AI-powered products, optimizing my health with data, and figuring out how to build tools that help people make better decisions about their lives.
A Decade of Impact
Reporting Data Analyst IV
Oct 2024 — Present- Built 5+ critical dashboards end-to-end for tracking Fraud Policy KPIs across the organization
- Spearheaded migration of 10+ dashboards to QuickSight, enhancing data quality and accessibility
- Led cross-functional collaboration for the Fast Funding project reporting framework
Marketing Data Analyst
Dec 2023 — Sep 2024- Partnered with PMs to drive 25+ global marketing campaigns for Azure and Office products
- Drove customer engagement by 20% and new customer acquisition by 25%
- Collaborated with Growth Managers and Data Engineers to optimize in-product campaigns
Business Intelligence Engineer
Aug 2022 — May 2023- Led search optimization for US and India markets, monitoring CTR and relevance metrics
- Collaborated with ML scientists to refine search ranking, achieving 20% engagement lift
- Engineered robust ETL pipelines using AWS Glue and S3 for multi-market data aggregation
Product Analyst
Apr 2020 — Jan 2022- Enhanced potential customer revenue identification by 12% via automated reports
- Revamped ETL procedures, achieving a 95% reduction in data inconsistencies
- Streamlined analytical workflows using Azure Data Studio and automated pipelines
Data Analyst
Feb 2018 — Apr 2020- Built data models resulting in a 50% improvement in detecting fraudulent profiles
- Implemented ML algorithms achieving 60% recall rate in identifying abusive orders
- Enabled real-time abuse monitoring using Tableau dashboards for Shopping teams
Selected Case Studies
Fraud Detection System
Machine Learning for Shopping Trust & Safety
Google Shopping faced growing losses from fraudulent merchant profiles and abusive orders, with existing rule-based systems missing sophisticated attack patterns.
Built ML classification models to detect fraud signals, combining behavioral features with transactional patterns. Created real-time Tableau monitoring dashboards.
Search Optimization
Multi-Market Search Ranking at Scale
Search relevance and engagement metrics across US and India markets needed optimization, with different user behaviors requiring market-specific tuning.
Partnered with ML scientists to design A/B experiments, built ETL pipelines with AWS Glue for cross-market data, and validated ranking algorithm changes rigorously.
Global Marketing Analytics
Data-Driven Campaign Strategy at Scale
Azure and Office needed a unified analytics framework to measure and optimize 25+ concurrent global campaigns across diverse markets and products.
Established KPI frameworks with Product Managers, built metric monitoring systems, and partnered with Growth teams to optimize in-product campaign performance.
What I Work With
Skill distribution across core competencies
Analytics & Testing
Languages & Frameworks
BI & Visualization
Cloud & Engineering
AI & Machine Learning
What I'm Building Next
Beyond the day job — exploring the intersection of AI, data, and products that help people make better decisions.
AI Life Dashboard
A personal AI dashboard that pulls together your health, tasks, finances, and relationships into one visual view — then uses AI to prioritize what actually matters today.
Product ConceptAI Analytics Engine
Helping businesses implement AI into their existing analytics workflows — turning slow, manual data work into fast, AI-powered insight engines.
Service / SaaSHealth Intelligence
A platform that analyzes your health data — labs, wearables, diet logs — and gives personalized, data-backed nutrition recommendations tailored to your body.
Health TechEducation & Certifications
Master of Science — Business Analytics
W. P. Carey School of Business, Arizona State University
Convolutional Neural Networks
Structuring ML Projects
Improving Deep Neural Networks
Neural Networks & Deep Learning
GitHub Projects
Sleep Data Analysis
Statistical modeling and hypothesis testing of sleep efficiency data from fitness trackers and heart-rate monitors using ANOVA.
Image Classification
Deep learning model for large-scale product image classification using convolutional neural networks.
Employee Turnover Prediction
Complete guide to predicting employee departures using machine learning — feature engineering, model comparison, and business insights.