What You will Do

• Apply rigorous statistical methods to analyze complex, high-volume datasets and extract meaningful insights.
• Design and execute experiments (e.g., DOE, hypothesis testing frameworks) to support product development, process optimization, and quality improvement.
• Develop, validate, and maintain statistical models, ensuring proper assumptions, diagnostics, and interpretability.
• Partner with engineers, scientists, and other stakeholders to frame problems statistically and guide data-driven decisions.
• Create dashboards and analytical tools that communicate variability, uncertainty, and key performance metrics effectively.
• Ensure reproducibility and robustness of analyses through proper documentation, version control, and statistical best practices.
• Contribute to the development of standardized statistical methodologies, reusable code libraries, and analytical workflows.
• Integrate statistical analysis into operational and digital platforms where appropriate.

About You

• Deep expertise in statistical inference, regression modeling, experimental design (DOE), and multivariate methods.
• Strong programming skills in R or Python, with emphasis on statistical computing, reproducible analysis, and data wrangling.
• Proven ability to translate complex statistical results into clear, actionable insights for both technical and non-technical stakeholders.
• Strong communication skills, including presenting statistical findings, assumptions, and limitations in industrial research setting.
• Experience designing, analyzing, and interpreting experiments (e.g., A/B testing, process optimization studies).
• Familiarity with data visualization and reporting tools (e.g., Power BI, Tableau).
• Working knowledge of SQL and modern data environments (e.g., Databricks, Azure, AWS, Snowflake) is a plus.
• Ability to work independently and collaboratively within cross-functional teams.

Skills/Qualifications

• PhD or Master’s degree in Statistics, Biostatistics, Applied Mathematics, or a closely related quantitative field (Data Science or Engineering considered with strong statistical emphasis).
• For Master’s candidates, a minimum of 3+ years of industry experience is required; experience in chemical, manufacturing, or process industries is a plus.
• Candidates with hands-on experience in experimental design, causal inference, and statistical modeling in real-world industrial settings.
• Candidates with a demonstrated ability to balance statistical rigor with practical business impact are especially encouraged to apply.

Your Benefits

EEO Statement