Senior Applied Statistician

About the role

Location: On-site, Portsmouth, NH. Relocation assistance is available for eligible candidates and their families.

As a key member of the Integrated Biologics Technical Operations Digital team, the Sr. Applied Statistician uses industrial statistics to improve manufacturing control and process understanding. The position designs control charts, assesses capabilities, and reduces variation. Working with multiple teams, the expert turns data into practical actions and builds site-wide statistical skills.

What you will get

• 401(k) plan with competitive company matching.
• A collaborative and inclusive work environment.
• Opportunities for career growth and development.
• Access to cutting-edge technologies and tools.
• Competitive compensation and benefits package.
• 401(k) matching plan with competitive company matching.
• Supportive leadership and mentoring.
• Commitment to ethical and sustainable practices.

Benefits

Access to our full list of global benefits:

What you will do

• Lead GMP Statistics: Drive statistical strategies for manufacturing to monitor processes and reduce variation.
• Manage Control Charts: Design real-time and offline charts to track critical quality parameters.
• Analyze Process Performance: Use advanced data methods to evaluate process capability and trends.
• Improve Process Robustness: Find variation sources and partner with teams to improve consistency.
• Design Data Strategies: Build data collection plans, measurement system analyses, and experiment designs.
• Ensure Regulatory Compliance: Align data and validation activities with FDA and ICH guidelines.
• Train and Align Teams: Guide global statisticians and train site workers in statistical thinking.

What we are looking for

• Bachelors of Science in Statistics, Computer Science, IT or related field Engineering.
• 5+ years of experience in industrial statistics, manufacturing, and process control is required, together with a passion for using statistical thinking to improve operational performance and build statistical capability across sites.
• Experience with modern statistical development environments, including cloud computing, Git, containers and DevOps practices, enabling reproducible, scalable statistical analyses beyond locally executed scripts.
• Deep understanding of experimental design (DoE) concepts to plan, execute and analyze multi-factor experiments to optimize the process parameters, identify root causes of defects and validate engineering changes.
• Deep theoretical and practical knowledge of acceptance sampling plans, multivariate statistical process control (MSPC), Hotelling's T² and generalized variance control charts, measurement system analysis, and Six Sigma methodologies.
• Advanced proficiency in statistical software and coding languages such as R, Python, TIBCO Statistica, SIMCA or Minitab.
• Strong communication and presentation skills to explain statistical concepts to plant operators and senior leadership.