Resume

Aamod Sathe

Head of Data & Analytics · Sunnyvale, CA · aamod.sathe@gmail.com · linkedin.com/in/aamodsathe

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Summary

Data and analytics leader with 20+ years building analytical functions, AI-native systems, and data infrastructure at scale. Consistent operating philosophy across every role: automate before you hire, treat internal operations as a product, build systems that scale ahead of growth. Has run executive metrics forums and business reviews at Google, Meta, and Vanta; led DS organizations of 60+ globally at Meta; and driven major business decisions — including the deprecation of a large Meta product line — through the quality of analytical evidence. Currently building the AI-native analytics function at Vanta while independently shipping AI products using Claude Code. Player-coach by orientation.

Experience
VantaMay 2026 – PresentCurrent

Head of Data & Analytics

  • Built MCP-based self-service layer that encodes business rules and data contracts at the infrastructure level — 80%+ of company data questions answered without analyst involvement at near-100% accuracy
  • Built LLM-based transcript parsing pipeline end-to-end: annotation framework, ground truth baselines, root cause diagnosis of a chunking failure the benchmarks had missed, fine-tuned production model at 88–92% accuracy at a fraction of prior API cost
  • Owns the weekly company metrics update and forum for the CEO and senior leadership team: defines what numbers appear, shapes the narrative, explains what is driving revenue and usage trends
  • Rebuilt company KPI framework from scratch — each metric explicitly linked to a decision the business can make, with driver trees connecting top-line trends to underlying levers
  • Revamped the full data architecture on dbt and BigQuery in six months; designed the semantic metrics layer that makes the same number appear regardless of who queries it or what tool they use
  • 40% headcount growth in four months; highest manager favorability gain at this level company-wide
MCPLLM EvaluationdbtBigQueryGCPSemantic Metrics LayerExecutive Metrics Forum
MetaJan 2025 – Mar 2026

Director of Data Science, Enterprise AI Platform

  • Built agentic analytical infrastructure for Meta's internal AI developer platform (70,000-engineer org) — natural-language-to-query systems and automated anomaly detection agents
  • Reduced data investigation cycle time 40%; drove AI-driven analytical output from 0 to 70% in 18 months
  • Defined evaluation frameworks, benchmark datasets, and guardrail metrics for AI model assessment — establishing what counts as a genuine performance improvement versus a measurement artifact
  • Set data quality and reproducibility standards across a large distributed technical organization
Agentic ToolingNL-to-SQLLLM EvaluationAnomaly DetectionGuardrail Metrics
MetaOct 2021 – Dec 2024

Director of Data Science, Reality Labs

  • Led 60+ person global DS organization across US and Singapore; set joint DS + DE strategy across 8 product lines (Quest, Portal, Ray-Ban Smart Glasses, Horizon Worlds)
  • Ran the executive business review and metrics forum for all of Reality Labs — owned the structure, content, and cadence; built the KPI framework across a multi-product, multi-business-model portfolio
  • Drove the deprecation of Portal (Meta's consumer video calling hardware) through analytical evidence: showed Portal was generating no meaningful north star metrics movement while carrying significant cost. Recommendation was directionally unpopular but held up — Portal was discontinued
  • Built the experimentation framework for ranking and recommendation systems: objective function design, guardrail metrics, counterfactual analysis, and governance standards that prevented metric drift
Executive Business ReviewKPI Frameworks60+ Global TeamExperimentation RigorProduct Deprecation
MetaApr 2020 – Oct 2021

Director of Data Science, Ads

  • Scaled DS team from 12 to 50+ in one year while maintaining production quality standards — hiring process, onboarding infrastructure, and quality gates
  • Built A/B testing, switchback experiment, and causal inference infrastructure connecting model changes to measurable P&L outcomes
  • Delivered $1B+ in incremental annualized revenue through data-driven product improvements
  • Partnered with Finance and senior leadership on the analytical frameworks that informed resource allocation and strategic planning
Revenue AnalyticsCausal InferenceA/B Testing at ScaleTeam Scaling$1B+ Impact
GoogleJan 2016 – Apr 2020

Group Analytics Manager, Consumer Data Science

Group Lead — Ads Relevance, Ranking & Operations Analytics · Nov 2018 – Apr 2020· Promoted to L7.5
Lead Analytics Manager — Google Ads Marketing Analytics · Jan 2016 – Nov 2018
  • Led analytics operations for Google Ads relevance and ranking ML systems — measurement infrastructure, evaluation frameworks, 70+ analytics staff globally
  • Ran executive metrics forum for Google Ads Marketing: defined KPIs and driver metrics, delivered weekly analytical narrative on growth, plan variance, and next actions
  • Built self-serve analytical tooling on large behavioral datasets; established reproducibility and data quality standards across a distributed organization
Executive Metrics ForumML System EvaluationGlobal Team OpsSelf-Serve Analytics
FacebookJul 2014 – Dec 2015

Head of SMB Analytics

  • Founded the analytics function from scratch for Facebook's B2B small business advertising platform — defined operating model, built data infrastructure, established GTM analytics capability
  • Delivered pipeline tracking, lead scoring, sales productivity metrics, and operational reporting with no prior infrastructure and no playbook
From-Scratch BuildGTM AnalyticsB2B SaaS MetricsEarly-Stage Product Analytics
PayPalMay 2009 – Jul 2014

Director of Product Analytics

  • Built stochastic forecasting models for capacity and growth planning and financial data pipelines connecting product performance to unit economics and margin
  • Developed behavioral cohort models for operational decision-support; analytical frameworks adopted company-wide; presented directly to the CEO
Stochastic ForecastingUnit EconomicsFinancial AnalyticsCEO-Level Communication
eBay2005 – 2009

Manager / Sr. Manager, Analytics

  • Built production ML systems at internet scale — trust and safety forecasting, fraud detection, community health signals, and capacity modeling
  • Each system designed to turn model output into an operational decision with direct business consequences
Trust & SafetyFraud DetectionProduction MLOperational Analytics
Skills
AI & MLLLM pipelines, MCP, agentic tooling, model evaluation, fine-tuning, anomaly detection, NL-to-SQL, Claude Code
AnalyticsExecutive metrics forums, KPI framework design, A/B testing, causal inference, stochastic forecasting, cohort analysis
Data Infrastructuredbt, BigQuery, Snowflake, GCP, Airflow, Spark, Presto, semantic metrics layer design, dimensional modeling
LeadershipDS + DE joint function leadership, global team management (60+), from-scratch function build, player-coach
TechnicalPython, SQL, Pandas, Scikit-Learn, dbt, BigQuery, GCP, Snowflake, Airflow, MCP, Spark
DomainsB2B SaaS, enterprise security, advertising platforms, payments, developer platforms, consumer hardware
Education
MS, Operations Research & Electrical Engineering
Pennsylvania State University · 2001 – 2003
BS, Electrical Engineering
Mumbai University · 1997 – 2001