Jobs / United States / Adobe INC
Data Scientist
Adobe INC · 🇺🇸 2 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 1,036 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 221 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Adobe INC paid sponsored hires in similar roles170 certified filings for “Machine Learning Engineer” (Data Scientists) in CA: $164k–$215k, median $184k. Most were filed at wage level II (45%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Adobe INC
The US Department of Labor certified 1,036 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 221 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Adobe INC →
About the role
The Opportunity Adobe Digital Insights (ADI) has been a leading authority on the global digital economy since 2013, building its analysis on trillions of visits, billions of online transactions, and the prompts behind billions of AI-generated assets crafted with Adobe Firefly. ADI works with creators, marketers, and business leaders, up to C-level leadership at Adobe’s largest customers, to help them understand how the digital economy is shifting and how their business is performing relative to industry peers using Adobe’s unique data. ADI’s mission is to inspire and delight all of Adobe’s audiences with leading, credible, differentiated, data-driven insights . We are transitioning to an agentic AI operating model, where LLM-powered agents are embedded across the end-to-end insights lifecycle, from raw data to business-ready insight products to audience-ready narrative. This role puts you in the middle of that work as a hands-on analyst turning Adobe’s data into the insights and stories our audiences rely on. Role Summary We are seeking a Data Scientist to support ADI’s digital economy work first and foremost. You will query and develop large datasets into trusted, repeatable insights. You will build the digital economy metrics and reports ADI is known for, and stepping in wherever the team needs analytical horsepower, from analysis of US dollar inflation to benchmarking critical web metrics. This is a hands-on analysis role for someone who loves finding the story in the data and getting it right. This is a full-stack role: you will work end to end from raw data through processing and analysis to the data products downstream users depend on. Along the way you will collaborate with engineering, analysts, architects, product managers, and leadership, becoming a go-to ADI subject-matter expert. What you'll Do • Own your work across the whole stack — from raw data and processing, through analysis, to data products downstream users and dashboards depend on. • Query, prioritize, and mine large structured and unstructured datasets (Adobe Analytics, Experience Cloud, CJA, and licensed sources) to produce accurate, defensible insights. • Build and maintain the recurring analyses, metrics, and indices behind ADI’s digital economy reporting, turning clean inputs into trusted outputs. • Flex to support any ADI topic as priorities shift across creativity trends, document efficiency, traffic based on data analysis, and product insights. • Turn analysis into clear narratives and visualizations that non-technical audiences can understand and act on. • Run ad-hoc deep dives and answer time-sensitive questions from collaborators across Adobe. • Work AI-natively using ADI’s AI tools and agents to speed up exploration, analysis, and drafting, while keeping a careful human eye on quality and consistency. • Partner with engineering to define data requirements and improve the pipelines and datasets you rely on. What you need to succeed • A degree or equivalent experience in a quantitative field (economics, statistics, mathematics, data science, or similar). • 4–6 years turning data into insight in an analytical, data science, or research role. • Strong data-analyst and insights skills querying with SQL and analyzing with Python to answer real business questions, not modeling for its own sake. • AI-native: proficient using AI and agentic tools to accelerate exploration, analysis, and drafting, with a careful human eye on quality. • Hands-on experience with Databricks (or a comparable large-scale data platform). • Strong analytical and quantitative problem-solving, forming hypotheses, testing them, and synthesizing clear recommendations. • A knack for data storytelling: explaining complex findings simply, in both writing and visuals.