Senior Field Scientist - Chicago

• 5–8+ years in sales engineering, data science, analytics consulting, or a similar technical pre-sales role in B2B SaaS, data, cloud, or AI.
• A track record leading research implementations that validated a complex enterprise solution and moved a deal to close.
• Strong data analysis with scientific rigor — you can design an experiment and process large-scale enterprise data sets without hand-waving the assumptions.
• Advanced Python (or equivalent) for data preparation, quality testing, and statistical analysis.

• Background at a measurement or market-research firm, a media or creative agency, or the analytics function of a large advertiser.
• Field studies or research implementations for data, cloud, or AI in a marketing context.
• Prior work as a senior data analyst, business analyst, or technical consultant with experimental design experience.
• Familiarity with enterprise procurement and security review processes.
• Startup or high-growth experience scaling research methodology.
• Advanced technical certifications (AWS Solutions Architect, GCP Professional) or expert-level AI/ML training.
• Exposure to value engineering, ROI modeling, and business case development.
• Previous startup or founder experience.

• Design and execute complex field studies that test hypotheses about marketing effectiveness and validate Alembic's transformational value.
• Lead data collection and requirements gathering with senior customer stakeholders, treating each engagement as a scientific research opportunity.
• Apply rigorous analytical methodology to prepare and process customer data, ensuring scientific validity at enterprise scale.
• Develop and test hypotheses about marketing performance, using experimental design principles to structure customer engagements.

• Present findings to C-level and senior customer stakeholders, translating complex analytical results into business impact.
• Serve as the scientific presence on the ground for Chicago-area accounts — building the working relationships with analytics, media, and finance teams that let a study actually get the data it needs.
• Collaborate with Enterprise AEs and Product to align research methodology with strategic objectives and ensure scientific rigor supports the sales process.
• Drive scalable research processes and best practices across the field science team.
• Mentor and develop junior field scientists in experimental design and analytical method.

• Contribute to product roadmap discussions based on customer technical feedback and research outcomes.
• Establish frameworks for replicable field studies that can be applied systematically across engagements.

• Hands-on experience with marketing measurement — marketing mix modeling, multi-touch attribution, incrementality and lift testing, geo experiments, or holdout design — and a clear-eyed view of what each method can and can't establish.
• Deep experience with data platforms, cloud infrastructure, or AI solutions.
• Excellent communication and presentation skills for sharing findings with C-level executives.
• Strong problem-solving mindset and scientific thinking.
• Collaborative, proactive, with team leadership experience.

• High-impact research with elite clients: You'll run field studies with Fortune 100 companies making multimillion-dollar marketing decisions — studies that matter, for clients that move the industry.
• A product that validates itself: You're not pushing features. You're running analysis that demonstrates 10–100x improvements and makes sophisticated prospects ask "how is this scientifically possible?"
• The method is the moat: Next-generation attribution grounded in mathematical physics — dynamical systems applied to messy enterprise data — running on one of the world's fastest private supercomputers.
• First-mover advantage: You'll be proving something that has never existed before, which is a real edge in every analytical conversation you have.
• Series B momentum, real ownership: Meaningful equity at a Series B company that's raised $145M, with proven product-market fit and Fortune 100 traction.

• You'd rather demonstrate an established, commoditized product with a well-defined playbook than do consultative scientific work that has to earn belief every time.
• You want a fully built-out research process rather than helping define our field study methodology through actual experimentation.
• You prefer static technical demos over dynamic research that adapts to what the data and the market tell us.
• You want a fully remote role. This one is deliberately local — the in-person time with customers is the job, not a formality.

Alembic is the pioneering Causal AI platform. We help the world's largest enterprises move past correlation to prove what actually drives business outcomes — the question marketing and growth teams have never been able to answer with confidence. Fortune 100 companies including Nvidia, Delta Air Lines, and Mars use Alembic to make multimillion-dollar decisions on trusted, causal evidence.

We're backed by a $145M Series B from WndrCo (founded by Jeffrey Katzenberg), Jensen Huang, Joe Montana, Prysm Capital, and Accenture. Our models run on our own NVIDIA DGX SuperPOD built on Grace Blackwell infrastructure — one of the fastest private supercomputers in the world. (We've melted GPUs getting here.)