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