Data Science Engineer 6

Adobe•San Francisco, CA

11d•$190,800 - $349,000

About The Position

Adobe is reimagining what creativity looks like in the age of AI — where generative models, intelligent agents, and human imagination work together to make the creative process faster, smarter, and more expansive. As Director, Data Science & Strategy – Agentic Product, you will lead Data Science and Strategic Insights for Adobe's Agentic team, spanning Firefly and third-party agents. You will help shape how AI augments creators, automates routine work, and extends Adobe's creative intelligence to new surfaces and audiences. Adobe's creative capabilities are increasingly in demand across the broader AI ecosystem. Our Agentic Product team is doing two things in parallel: building a central agentic platform anchored in Firefly, and packaging and publishing Adobe's unique creative and productivity capabilities across a rapidly expanding landscape of third-party AI surfaces — chat portals, desktop and mobile operating systems, and vertical applications across industries. The mission is to be the creative agent of the AI era: embedded everywhere people create, and the force that brings them to Adobe. This work requires a leader who combines deep technical fluency in data and AI systems with the strategic judgment to translate those capabilities into business impact. In the agentic era, that means going beyond traditional analytics — understanding how autonomous systems plan, reason, and act; designing data infrastructure that serves both human and machine consumers; and building the evaluation frameworks needed to trust and govern AI-generated outputs. Equally important is the ability to operate with clarity in ambiguity, knowing where automation should stop, and human judgment must lead. The ideal candidate brings intellectual honesty, a high bar for quality, and the cross-functional influence to shape not just what the data says — but what the organization decides to do with it. This is a rare opportunity to define Adobe's presence in the next generation of creative software distribution. The person in this role will partner across product, engineering, partnerships, corporate strategy, and GTM — using data and insight to inform a scalable strategy that grows Adobe's first-party products while compounding reach across third-party surfaces, ensuring every experience reflects the quality and creative intelligence Adobe is known for. This is a senior IC role and requires hands on experience to build the systems we need – ready to roll up sleeves, get in the trenches.

Requirements

10+ years of experience in data science, analytics, or strategic insights, ideally within AI-driven products, creative software, or platform ecosystems.
Deep fluency in the mechanics of agentic systems — how agents plan, act, and are evaluated — with the ability to design measurement frameworks that capture performance, quality, and business impact across both first-party and third-party surfaces.
Expert-level command of experimentation methodology — A/B testing, causal inference, and multivariate analysis — paired with a strong PLG instinct for the metrics that drive activation, retention, and growth in product-led motions.
Proven ability to build AI-native analytical workflows, using LLMs and agentic tooling to move beyond manual analysis and surface insights at scale and speed.
Exceptional strategic thinking, with the ability to translate complex data signals into clear, opinionated recommendations that influence roadmap and go-to-market decisions.
Strong executive presence and communication skills — able to present findings with clarity and conviction to senior leaders, and to align cross-functional teams around a shared analytical framework.
Comfort operating in ambiguity and defining new approaches in spaces where the playbook doesn't yet exist.
Passion for Adobe's mission and a genuine belief that AI should amplify, not replace, human creativity.

Responsibilities

Define the measurement framework for agentic products — establish the metrics, taxonomies, and evaluation standards that capture how AI agents perform, where they create value, and how success is defined across both first-party and third-party surfaces
Build AI-native analytical workflows — leverage LLMs and agentic tools to continuously and proactively analyze data, generate insights and report anomalies at scale
Instrument and accelerate agentic experimentation — design and own the experimentation infrastructure and statistical frameworks needed to run rapid A/B and multivariate tests across agentic surfaces, translating PLG signals — activation rates, feature adoption, retention curves — into rigorous, reproducible insights that drive product iteration at speed
Shape product and GTM strategy through data — serve as a strategic thought partner to product, partnerships, and GTM leads, translating complex data signals into clear recommendations that influence roadmap prioritization and go-to-market decisions
Design the strategic intelligence layer — develop repeatable frameworks for competitive analysis, opportunity sizing, and performance benchmarking that both the Firefly and third-party agent teams can act on with confidence
Drive insight governance and standards — establish a shared language for how data is interpreted and used across teams, ensuring analytical outputs are consistent, trustworthy, and actionable — and that the right humans are in the loop where agent judgment alone is insufficient