We are looking for a Research Statistician – Innovation & Data Science who is passionate about applying statistics, experimental design, and data science to solve scientific, innovation, and customer challenges.
You will serve as a key statistical partner to scientists, chemists, engineers, technical sales teams, and customers—helping teams design smarter experiments, extract meaningful insights from data, and make faster, more confident decisions across growth, adjacent innovation, and incremental improvement projects.
A key part of your role will be building statistical capability across the organization through training, coaching, and hands-on project support in Design of Experiments (DOE), statistical analysis, optimization, and customer trials. You will also help advance the application of machine learning, artificial intelligence, and advanced analytics to innovation challenges.
Provide statistical leadership and consulting across innovation projects, from early exploration through optimization, validation, and customer implementation.
Partner with scientists, chemists, and engineers to translate technical questions into effective experimental strategies.
Design and analyze experiments using appropriate DOE methodologies, including screening, factorial, response surface, mixture, custom/optimal designs, and multi-response optimization.
Apply statistical modeling and analysis to laboratory, application, pilot, manufacturing, and customer-generated data, translating results into clear insights and actionable recommendations.
Partner with technical sales teams and customers to design and interpret statistically sound customer trials, product comparisons, and validation studies.
Develop and deliver practical training in DOE, statistical analysis, data interpretation, and customer trial design for scientists, engineers, and technical sales professionals.
Coach project teams in applying statistical methods independently and develop practical tools, templates, and best practices to strengthen organizational capability.
Use statistical approaches to reduce experimental workload, accelerate learning, and improve the quality and speed of innovation decisions.
Collaborate on machine learning, artificial intelligence, predictive modeling, and advanced analytics projects, ensuring appropriate statistical rigor, validation, robustness, and interpretation.
The opportunity to have a visible impact on innovation and growth by solving challenging scientific, engineering, and customer problems.
A collaborative environment spanning scientific disciplines, technologies, applications, commercial teams, and customers.
A diverse portfolio of projects, from exploratory research and product development through customer validation and commercialization.
The opportunity to shape and strengthen statistical and DOE capabilities across the organization.
Opportunities to expand your expertise at the intersection of statistics, experimental science, machine learning, and artificial intelligence.
An environment that values curiosity, continuous learning, collaboration, and new ideas.
An advanced degree in Statistics, Applied Statistics, Data Science, or a related quantitative/scientific discipline, with deep formal training and demonstrated expertise in applied statistics. A Ph.D. or equivalent level of advanced statistical expertise and relevant applied experience is strongly preferred.
Demonstrated expertise in Design of Experiments (DOE), statistical modeling, optimization, and analysis of experimental data.
Experience applying statistical methods to complex scientific, engineering, product development, manufacturing, or customer problems.
Advanced proficiency with statistical and data-analysis software such as JMP, Minitab, R, Python, SAS, or comparable platforms; expertise in JMP and/or Minitab is highly valued.
Strong knowledge of regression, analysis of variance, multivariate methods, model development and validation, uncertainty, and statistical visualization.
The ability to understand the underlying scientific or business problem and select an appropriate statistical approach—not simply analyze a provided dataset.
Excellent communication and presentation skills, with the ability to make complex statistical concepts practical and understandable for diverse audiences.
A collaborative and consultative approach, with the ability to work effectively with and influence customers, scientists, technical sales professionals, and business leaders.
An interest and demonstrated ability in teaching, coaching, and developing statistical capability in others.
Curiosity about chemistry, materials, processes, applications, and the customer challenges behind the data.
Strong interest in machine learning and artificial intelligence, with the ability and motivation to contribute to projects applying these technologies.
Experience with Python or R and exposure to machine learning, predictive modeling, or advanced analytics is highly desirable.
Experience in chemicals, specialty materials, formulations, materials science, industrial R&D, or a related technical environment is preferred.
Competitive salary and benefits package. The U.S. base salary range reasonably expected to be paid for this position is $98,000 - 140,000.00 per year. Since actual compensation packages are based on a variety of factors unique to each candidate we may ultimately pay more or less than the posted base salary range. Total compensation for this role also includes bonus and/or other incentives
16 or more weeks of maternity/paternity and co-parenting leave, according to local regulations.
Training platform for all employees.
Free well-being sessions (physical and psychological).
This is a hands-on, collaborative, and influential technical role. You will move between statistical analysis, scientific problem-solving, teaching and coaching, and interactions with customers and commercial teams.
You should be comfortable asking challenging questions, influencing experimental approaches, and helping multidisciplinary teams understand what the data can—and cannot—support.
Travel may be required to support collaboration with technical teams and customers.
About us
Apply on Syensqo’s careers page