ML Solution Consultant

Thank you for your interest in Uncountable Implementations!

About Uncountable

Science moves slowly — not because researchers aren't brilliant, but because their tools haven't kept up. Uncountable is changing that. We build a unified R&D platform used by the world's leading chemists, material scientists, and biologists to dramatically accelerate how new products are discovered, developed, and brought to market.

Founded by engineers from MIT and Stanford, and trusted by enterprise R&D organizations across chemicals, pharmaceuticals, advanced materials, and food & beverage, Uncountable is on a mission to accelerate industrial R&D by an order of magnitude. We're a high-impact team that moves fast and gives people real ownership from day one.

The Role

Machine learning is only as powerful as the people who can apply it in context — and in industrial R&D, that context is everything. As an ML Solution Consultant at Uncountable, you'll be the person who bridges deep technical expertise in data science and statistical modeling with a genuine understanding of how R&D scientists think, experiment, and make decisions.

You'll work directly with leading R&D organizations to deploy Uncountable's AI capabilities, guiding customers through the full arc of adoption: from understanding their scientific challenges and data structures, to designing optimal experimentation strategies, to ensuring they're extracting real, measurable value from our platform's ML tools.

This is not a back-office data science role. You'll be customer-facing, highly autonomous, and operating at the frontier of applied ML in science — advising PhD-level researchers and R&D directors on how to use AI to accelerate their most important work. You'll also have a direct line to product and engineering, shaping how our platform evolves based on what you see in the field.

If you want to do meaningful applied ML work that reaches the real world — and have the communication skills to bring scientists along with you — this role is for you.

What You'll Do

Deploy AI Capabilities with Customers

• Partner directly with R&D teams at enterprise customers to understand their scientific challenges, data environments, and experimentation workflows
• Guide customers through onboarding onto Uncountable's ML tools, ensuring data is well-structured and models are configured to reflect their specific scientific context
• Help customers interpret model outputs, act on recommendations, and build confidence in AI-driven experimentation over time

Serve as a Technical and Scientific Expert

• Act as a subject-matter expert in statistical modeling, machine learning, and experimental design — advising customers on strategies that maximize the value of their data
• Translate complex ML concepts into clear, actionable guidance for scientists and R&D leaders who may not have a data science background
• Troubleshoot modeling challenges, identify data quality issues, and design solutions that make the science work

Drive Cross-Functional Impact

• Collaborate closely with Uncountable's product and engineering teams, bringing structured customer feedback and real-world usage patterns to inform platform development
• Identify recurring challenges and opportunities across customer engagements that can be addressed through new features or improved workflows
• Contribute to internal knowledge-sharing on ML best practices, customer patterns, and domain-specific modeling approaches

Requirements

• ML and data science depth: Strong foundation in machine learning, statistical modeling, or applied statistics — comfortable with experimental design, model evaluation, and working with messy, real-world scientific data
• Scientific domain fluency: Experience working with R&D data, physical experimentation workflows, or scientific datasets — enough to speak credibly with researchers about their work
• Communication: Exceptional ability to translate technical concepts into business and scientific value for a wide range of audiences, from bench scientists to R&D directors
• Software fluency: Comfort working with data science tools and environments (Python, statistical software, or similar); experience with scientific or R&D software a strong plus
• Autonomy: Ability to manage customer engagements independently, navigate ambiguity, and drive toward outcomes in a fast-paced environment

Preferred Qualifications

• M.S. or Ph.D. in a quantitative field such as Chemistry, Materials Science, Chemical Engineering, Physics, Data Science, or a closely related discipline
• Experience in a customer-facing technical role — solutions engineering, technical consulting, or pre/post-sales data science
• Exposure to product development processes in materials, chemicals, pharmaceuticals, food science, or adjacent industries
• Familiarity with Bayesian optimization, design of experiments (DoE), or active learning methods in applied settings

Why This Role

• Applied ML that reaches the real world: Your work accelerates R&D at organizations developing next-generation products — from sustainable materials to life-saving medicines. The models you deploy aren't research artifacts; they're tools scientists use every day
• Rare scope: You'll operate across scientific domains — coatings, polymers, pharmaceuticals, food science, advanced materials — developing breadth of expertise that's nearly impossible to build elsewhere
• Scientific credibility meets technical depth: This role is built for people who can hold their own both in a conversation about experimental design with a PhD chemist and in a technical discussion with a product engineering team
• Direct product influence: At our scale, what you learn in the field shapes what we build next. You'll have a real voice in Uncountable's ML roadmap
• High autonomy, high impact: You'll own your customer relationships and drive outcomes — not execute a playbook

Benefits

• Competitive base salary with performance bonus and meaningful equity
• Health and dental insurance
• 401(k) with employer contribution (US locations)
• Direct collaboration with a world-class engineering and data science team

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