SS Sid Shah Consulting
Fractional Data & AI Leadership

Data & AI strategy that ships.

I help enterprises turn data and AI into measurable business outcomes — setting the strategy, designing the prototype, advising execution alongside your teams, and bringing in specialists when needed. Two decades leading data science and AI across product, growth, marketing, finance, and go-to-market — at companies of every size, from startups to $100B+ enterprises.

Email me → See how I work
$40M
cost saved via AI-driven inventory & fulfillment optimization
1,000+
users on an agentic insights engine — week-long analyses in ~20 min
7–15%
media budget freed on $100M spend, MQLs & conversions held flat
90%+
quarterly accuracy on ML-based revenue forecasting
The Differentiator

Most leaders are broad or deep. The hard part is being both.

The rare thing isn't knowing data science, or knowing the business. It's being able to sit with a CFO and design how AI reshapes the finance function — then architect the prototype and stand up the team that makes it real. Twenty years on both sides of that line, and the value is in joining them.

Breadth — every function in the company

I've partnered as a data scientist and data leader with nearly every function: Product, Growth, Marketing, Sales, Customer Success, Finance, and Data Engineering. That cross-functional fluency means I can connect a marketing-spend decision to a finance forecast to a product-retention metric — because I've worked deeply in all of these areas.

Depth — strategy through execution

I operate at the strategy altitude — white papers on transforming a finance org with AI, enterprise data governance frameworks, growth strategy — and stay close enough to the technical floor to architect the right approach, design working prototypes, and advise execution hands-on. The same person who briefs your board can prove out the build with your teams — and bring in a trusted bench of specialists when the work calls for it.

One leader, every function — here's the signature result in each.
Product & Growth
PLG → 10% of ARR
Scaled product-led growth to ~10% of total revenue at a $1B/year company.
Marketing
7–15% freed
Media-mix modeling freed budget on $100M spend with MQLs & conversions flat.
Finance
$40M saved
AI-driven optimization cut cost; forecasting hit 90%+ quarterly accuracy.
Go-to-Market
10% less churn
Health & adoption scores lifted adoption ~10% and reduced churn.
AI & Agentic
1,000+ users
Agentic insights engine turned week-long analyses into ~20 minutes.
Data
$100B-scale
Enterprise data governance across structured and unstructured data.
Most leaders go deep in one column. The value is in delivering across all of them.
Capabilities

Six areas where I've led and shipped.

Each spans the full arc — framework, build, and operations. Tap any area to see representative work.

AI & Agentic Systems

Production AI, not slideware
  • Agentic insights engine, built from scratch. Conversational analytics over 50+ enterprise data sources — ask your data "how's the revenue forecast tracking?" or "which accounts are at risk?" and get analyst-grade answers, charts, and dashboards. Adopted by 1,000+ users, collapsing analyses that took a week into ~20 minutes. Built in-house with a team of five engineers — comparable vendor products run ~$250K/year.
  • Agentic GTM intelligence. Account-intelligence agents that fuse first-party and third-party web data to surface opportunities and generate rep-ready next-best-actions; deal-desk and pipeline-generation automation — built with rigorous evals, guardrails, and access controls.
  • Enterprise context & knowledge graphs. Built knowledge and context graphs at enterprise scale — the semantic backbone that lets agents reason over company-wide knowledge accurately, with the right context retrieved in a trustworthy, efficient way.
  • Agentic marketing planning & orchestration. Campaign strategy, planning, and orchestration run by agents with a human in the loop — doing the work of ~10 people and compressing two weeks of effort into two days.
  • AI-accelerated software development. Led adoption of AI across the software development lifecycle, cutting typical sprint work from two weeks to two–three days.
  • AI-enabled data governance. Applying AI to the governance problem itself, across both structured and unstructured data.

Data & Platforms

The foundation everything stands on
  • Data governance at enterprise scale. Led governance programs at $100B+ enterprises — covering both structured governance and unstructured governance (managing context for AI).
  • AI-ready data foundations. Modern data platforms and semantic layers that make enterprise data clean, governed, and ready for AI to consume.
  • Single sources of truth & enterprise metrics. SSOTs, North-Star and star-schema metric design, data-mart reporting, and executive dashboards that power company-wide decisions.

Product & Growth

User growth as the common thread
  • The GEAR framework — Growth · Engagement · Adoption · Retention. A framework I developed and operationalized for user growth, with the tracking system to run it. Applied to growth functions at billion-user consumer platforms and enterprise SaaS alike.
  • Product data science. Feature adoption, onboarding, and retention; cohort and journey analysis; in-app interventions like guides and tours.
  • Experimentation as a discipline. Selecting the right experimentation platform, defining best practices, and serving as the subject-matter expert who designs experiments and stands up rigorous launch testing.
  • PLG / product-led growth. Oversaw a product-led growth program that scaled from a small fraction of revenue to ~10% of total ARR at a $1B/year company — building the operational program and the data science that drives both user and customer growth.

Marketing & Advertising Science

Algorithmic, at scale
  • Media Mix Modeling. ML-based optimization of media spend across channels. On a $100M budget, freed up 7–15% of spend while holding MQLs and conversions flat — and productized the approach into a commercial marketing-cloud offering.
  • Attribution & algorithmic performance marketing. Optimized $2B+ in annual ad spend using modern-portfolio-theory-based methods; underlying work cited by the Wall Street Journal and Forbes.
  • Campaign analytics & campaign data science. Propensity and growth models, funnel analytics, and performance measurement.

Finance & Pricing

Forecasting, margins, optimization
  • ML-based revenue forecasting. Topline and segment-level forecasting models delivering 90%+ accuracy on a quarterly basis.
  • Margin analysis. Gross and net margin by team, product line, and segment — with the reporting to support it, surfacing 5–10% cost savings at a $1B company.
  • AI-driven optimization. Inventory, fulfillment, and scheduling optimization using mixed-integer programming — delivering ~$40M in cost savings while maximizing business outcomes like revenue.
  • Pricing model design. Subscription and consumption-based enterprise pricing, built in partnership with finance and product.

Go-to-Market

Pre- and post-sales, full lifecycle
  • Customer health & adoption scores. Data-science-driven scores blending product adoption, technical deployment, and contract health — paired with intervention playbooks by cohort and segment (enterprise vs. SMB motions). Drove ~10% higher product adoption and a corresponding reduction in churn.
  • Sales & GTM analytics. AI-driven sales plays, deal-flow automation and optimization, and pipeline and topline forecasting.
  • Customer Success partnership. Data-driven customer management, churn prediction, and intervention-effectiveness measurement across the full lifecycle.
Sid Shah
About Sid

Two decades turning data and AI into outcomes.

Sid Shah is a data science and AI leader who works at both the strategic and technical ends of the problem. He currently leads a 150+ person data, analytics, and AI organization at Palo Alto Networks, building production agentic AI systems and next-generation AI data foundations. Earlier, at YouTube, he led data science across Recommendations, Responsibility, and Growth at billion-user scale; built growth-focused data science teams from scratch at Google Maps; and led customer and product analytics at Adobe. His career began in algorithmic advertising at Efficient Frontier, optimizing more than $2B in annual ad spend.

What sets Sid apart is the rare combination of breadth and depth — fluent across nearly every function, and equally at home setting board-level strategy or building alongside the team. He holds a PhD and two master's degrees in engineering from the University of Michigan, and is a published researcher on AI safety.

Selected Experience

Two decades, at the companies that set the bar.

Palo Alto Networks
VP, Data, Analytics & AI2025 – present
Enterprise data & AI charter; production agentic systems across a 150+ person org.
New Relic
VP, Analytics & Data Science2023 – 2025
All data science across Product, Growth (PLG), Sales, Finance, and enterprise data products.
YouTube · Google
Director, Data Science2021 – 2023
Recommendations, Responsibility, and Growth at billion-user scale.
Google Maps
Director, Product Analytics2019 – 2021
Built a growth data science team from scratch; insights reshaped Maps growth strategy.
Adobe
Sr Director, Customer & Product Analytics2012 – 2019
Product Adoption Score, Media Mix Modeling product, and customer-value KPIs.
Efficient Frontier
Sr Director, Business Analytics2009 – 2012
Optimized $2B+ in annual ad spend; quarterly research cited by WSJ and Forbes.
Let's talk

Let's talk about where data and AI move your business.

Whether you need a fractional data & AI leader, a strategic advisor to your exec team, or someone who can set the vision, prove it out, and bring in the team to execute — start with a conversation.

siddharth.shah.phd@gmail.com LinkedIn →