Data Scientist – R&D Digitalization & Uncountable Platform

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.

Data Scientist – R&D Digitalization & Uncountable Platform (1-Year Contract)

The Qnity IT Technology Solutions team provides digital solutions that support data management, automation, computing, and analytics for R&D and engineering organizations.

We are seeking a scientifically minded Data Scientist whose primary mission is to maximize the value of the Uncountable platform for R&D teams. This role combines experimental design, data science, and data engineering to help scientists accelerate development cycles, optimize formulations and processes, and make better use of experimental data.

The successful candidate will partner closely with scientists to drive Uncountable adoption, deliver data-driven insights, and expand analytics and AI capabilities across R&D.

Core Responsibilities — Maximizing the Uncountable Platform

The heart of the role: put the platform to work for R&D and prove its value.

• 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.

• Develop and maintain data pipelines that ingest, extract, clean, integrate, and prepare data from diverse sources (e.g., laboratory systems, databases, spreadsheets, PDFs, images, and scientific datasets) for use within 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, integrated, 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 through faster development cycles, fewer experiments, and better-performing formulations and processes.

Extending Impact Beyond the Platform

Where the role grows once platform value is established.

• 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.

Technical & Scientific Partnership

• 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.

• Troubleshoot modeling challenges, identify data-quality issues, and design solutions that improve scientific decision-making.

Continuous Improvement & Collaboration

• Proactively identify gaps in current workflows, data infrastructure, or platform usage and propose improvements.

• Collaborate with global IT, digitalization, and R&D teams to align on best practices for data management, analytics, and platform adoption.

• Contribute reusable solutions, implementation patterns, and data standards that support scalable digitalization across the organization.

Required Qualifications

• Advanced degree in Materials Science, Chemistry, Physics, Data Science, Computer Science, or a related quantitative field.

• 2+ years of experience in data science, machine learning, scientific computi