Are you looking to power the next leap in the exciting world of advanced electronics? Do you want to help solve problems that drive success in the rapidly evolving technology and connectivity landscape? Then bring your problem-solving, passion, and creativity to help us power the next leap in electronics.
At Qnity, we’re more than a global leader in materials and solutions for advanced electronics and high-tech industries – we’re a tight-knit team that is motivated by new possibilities, and always up for a challenge. All our dedicated teams contribute to making cutting-edge technology possible. We value forward-thinking challengers, boundary-pushers, and diverse perspectives across all our departments, because we know we play a critical role in the world enabling faster progress for all. Learn how you can start or jumpstart your career with us.
The Qnity IT Technology Solutions team provides digital solutions that support data management, automation, computing, and analysis for R&D and engineering teams.
We are seeking a scientifically-minded Data Scientist whose primary mission is to help our R&D teams capture the full value of the Uncountable platform. Working hands-on in Uncountable’s visualization, statistics, and machine-learning tools, this person partners with scientists to explore their experimental data, design and run design-of-experiments (DoE) studies, and drive formulation and process optimization.
This is a build-and-grow role. The first priority is mastering the Uncountable platform and turning its capabilities into measurable wins for R&D. Over time, the role expands to developing analytical capabilities beyond the platform — extending the impact of data science across the R&D organization.
Core Responsibilities- Partner directly with R&D teams to understand their scientific challenges, data, and experimentation workflows, then translate them into DoE and optimization studies on the Uncountable platform.
- Use the platform’s visualization, statistical, and machine-learning tools to explore experimental data, surface key drivers and relationships, and recommend the next best experiments.
- Onboard and coach R&D scientists on the platform — ensuring data is well-structured and models are configured to reflect their specific scientific context.
- Help scientists interpret model outputs, act on recommendations, and build lasting confidence in model-guided experimentation.
- Deliver measurable value: faster cycles, fewer experiments, and better-performing formulations and processes.
- Develop custom analyses, models, and tools that complement Uncountable where its out-of-the-box capabilities stop short.
- Connect insights from the platform with other R&D and enterprise data to answer broader scientific and business questions.
- Build reusable methods, templates, and best practices that scale data science across R&D teams.
- Help shape the broader R&D data science and AI roadmap alongside IT and digitalization partners.
- Act as a go-to resource in statistical modeling, machine learning, and experimental design — advising R&D teams on strategies that maximize the value of their data.
- Translate complex 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.
- Proactively identify gaps in current workflows or platform usage and propose improvements.
- Collaborate with global IT and digitalization teams to align on best practices.
- Contribute to reusable solutions and scalable implementation patterns.
Required Qualifications
- ML and data science foundation: comfortable with machine learning, statistical modeling, or applied statistics — including experimental design, model evaluation, and working with messy, real-world scientific data.
- Scientific domain fluency: experience with R&D data, physical experimentation workflows, or scientific datasets — enough to speak credibly with researchers about their work.
- Platform aptitude: curiosity and ability to quickly learn and apply a specialized R&D platform’s ML and optimization tools. Hands-on Uncountable experience is a plus, not a requirement — we will train.
- Communication: ability to translate technical concepts into scientific and business value for audiences ranging from bench scientists to R&D leaders.
- Software fluency: comfort with Python, statistical software, or similar data-science environments.
- M.S. or Ph.D. in a quantitative field such as Chemistry, Materials Science, Chemical Engineering, Data Science, or a closely related discipline.
- Familiarity with Bayesian optimization, design of experiments (DoE), or active-learning methods in applied settings.
- Exposure to product-development processes in materials, chemicals, or adjacent industries.
- Ability to build capabilities beyond a single platform — e.g., custom models with Python ML libraries, dashboards, or data-visualization tools.
- Prior experience with R&D data or experimentation platforms (Uncountable or similar) and integrating their outputs with other analytics.
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Qnity is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability or any other protected class. If you need a reasonable accommodation to search or apply for a position, please visit our Accessibility Page for Contact Information.
Qnity offers a comprehensive pay and benefits package. To learn more visit the Compensation and Benefits page.
We use Artificial Intelligence (AI) to enhance our recruitment process.
Skills Required
- Experience with machine learning, statistical modeling, or applied statistics, including experimental design and model evaluation
- Experience working with messy, real-world scientific data
- Experience with R&D data, physical experimentation workflows, or scientific datasets
- Ability to quickly learn and apply specialized R&D platform machine learning and optimization tools
- Ability to translate technical concepts into scientific and business value for technical and leadership audiences
- Comfort with Python, statistical software, or similar data-science environments
- M.S. or Ph.D. in Chemistry, Materials Science, Chemical Engineering, Data Science, or a related quantitative discipline
- Familiarity with Bayesian optimization, design of experiments, or active-learning methods
- Exposure to product-development processes in materials, chemicals, or adjacent industries
- Ability to build custom models with Python machine-learning libraries, dashboards, or data-visualization tools
- Experience with R&D data or experimentation platforms such as Uncountable and integrating their outputs with other analytics
Qnity Electronics, Inc. Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Qnity Electronics, Inc. and has not been reviewed or approved by Qnity Electronics, Inc..
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Strong & Reliable Incentives — Performance-based bonus plans tied to individual and company results are a core part of the package. Feedback suggests these incentives are positioned as competitive and, in some roles, experienced as meaningful.
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Retirement Support — Retirement savings options are portrayed as strong, including a 401(k) with employer contributions. Some disclosures indicate automatic company contributions, reinforcing long-term financial support.
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Healthcare Strength — Medical, dental, vision, life, and disability coverage are presented as comprehensive with additional wellbeing programs and day-one eligibility signals. This breadth is framed to support physical and financial wellbeing.
Qnity Electronics, Inc. Insights
What We Do
Qnity Electronics, Inc. is a premier technology provider across the semiconductor and advanced electronics value chain. It specializes in providing high-performance materials and integration expertise to enable breakthroughs in AI, high-performance computing, and advanced connectivity. Its offerings range from semiconductor chip manufacturing solutions to high-speed transmission materials for complex electronic systems, serving as a critical partner in the global electronics ecosystem.

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