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
Senior Data Analyst
Oct 2023 — Present- Built 5+ critical dashboards end-to-end for tracking Fraud Policy KPIs, becoming the org's go-to resource for fraud analytics
- Spearheaded migration of 10+ dashboards to QuickSight, improving data freshness from daily to near real-time
- Led cross-functional collaboration across Engineering, Risk, and Product for the Fast Funding project reporting framework
- Mentored 2 junior analysts on SQL optimization and dashboard best practices, reducing their ramp time by 40%
Marketing Data Analyst
Oct 2023 — Sep 2024- Owned the analytics strategy for 25+ global marketing campaigns for Azure and Office, defining KPIs and measurement frameworks from scratch
- Drove customer engagement by 20% and new customer acquisition by 25% through data-driven campaign optimization
- Partnered with Growth Managers and Data Engineering to build an automated campaign performance pipeline replacing 15+ hours/week of manual reporting
- Established the team's A/B testing playbook, standardizing how marketing experiments were designed, measured, and reported
Business Intelligence Engineer
Aug 2022 — Aug 2023- Led search optimization for US and India markets, personally defining the CTR/relevance metric framework used across both regions
- Designed and analyzed A/B experiments with ML scientists to validate ranking algorithm changes, achieving 20% engagement lift
- Architected ETL pipelines using AWS Glue and S3 that unified multi-market data into a single analysis layer, adopted by 3 partner teams
- Onboarded and ramped 2 new BIEs on the team's data infrastructure and experimentation workflows
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
- Cut biweekly analytics delivery time by 33% by optimizing reporting workflows, freeing ~8 hours/week of team capacity
- Became the go-to resource for data pipeline troubleshooting across 3 product teams, informally mentoring new analysts on SQL best practices
Data Analyst
Feb 2018 — Apr 2020- Built production Python/ML models for Shopping fraud detection that reached 60% recall on abusive orders and cut transactional losses by 50%
- Designed the data models behind fraudulent profile detection, driving a 50% improvement in proactive detection
- Deployed Tableau dashboards with auto-alerting so the payments team could act on abuse in real time
- Partnered with engineering and policy to convert model outputs into platform-wide detection rules, scaling fraud defense across high-volume transaction paths
Selected Case Studies
FinRisk Analytics Platform
End-to-End Fraud Policy Intelligence at Scale
Intuit's FinRisk org needed a unified analytics layer across five product lines (Payments, Payroll, Bill Pay, Banking, Capital) to monitor fraud policy performance, pass regulator audits, and support a major onboarding risk overhaul.
I designed and built the full analytics stack from scratch — 16+ production dashboards, 20+ Superglue ETL pipelines, and 8 AIG tables. Led the Tableau-to-QuickSight migration, built regulator-facing IDV compliance dashboards, and designed the ONB 2.0 merchant mapping data model.
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.
I built Python/ML classification models combining behavioral features with transactional patterns, designed the data models behind fraudulent profile detection, and deployed Tableau dashboards with auto-alerting for real-time abuse monitoring.
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.
I personally defined the CTR/relevance metric framework, designed A/B experiments with ML scientists to validate ranking algorithm changes, and architected ETL pipelines using AWS Glue that unified multi-market data into a single analysis layer.
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.
I established KPI frameworks from scratch with Product Managers, built automated campaign performance pipelines replacing 15+ hours/week of manual reporting, and partnered with Growth teams to feed targeting fixes back into campaign strategy.
What I Work With
Skill distribution across core competencies
Analytics & Testing
Languages & Frameworks
BI & Visualization
Cloud & Data Engineering
AI & Machine Learning
AI Tooling & Automation
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
Career-Ops
AI-powered job search pipeline built on Claude Code — 14 skill modes, automated portal scanning, offer evaluation with A-F scoring, and PDF resume generation.
Ecoute — Live AI Transcription
Real-time transcription tool that captures mic and speaker audio simultaneously, then generates AI-suggested responses using GPT-3.5 during live conversations.
Portfolio Website
This site — built from scratch with vanilla HTML/CSS/JS, Canvas 2D particle networks, GSAP scroll animations, SVG radar charts, and an AI-powered chatbot.