Engineering Statistics and Data Analytics Manager (M5) - Onsite

RTX•East Hartford, CT

24d•Onsite

About The Position

Pratt & Whitney is seeking a visionary Engineering Statistics & Data Analytics Manager to lead our efforts in transforming complex engineering data into actionable strategic insights. You will bridge the gap between advanced statistical theory and practical engineering applications, overseeing a team dedicated to optimizing product & process quality, yield, and reliability. The ideal candidate is a "player-coach" who can dive into a Bayesian model on Monday and present a multi-year data roadmap to executive leadership on Tuesday.

Requirements

A Bachelor's degree in Science, Technology, Engineering, or Mathematics (STEMS) and 10 years prior relevant experience, or an Advanced Degree in a related field and 7 years prior relevant experience.
Relevant experience includes experience in an engineering-heavy industry (e.g., Semiconductors, Aerospace, MedTech, or Automotive), with at least 3 years in a leadership/management capacity.
Expertise in R, Python, or JMP/Minitab
Proficiency working with large-scale industrial datasets
Strong grasp of Machine Learning (ML) applications within physical systems
Proven ability to translate "p-values and neural nets" into business value for non-technical stakeholders.
U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance
The ability to obtain and maintain a U.S. government issued security clearance is required.
Active and existing security clearance required after day 1

Nice To Haves

Master’s or PhD in Statistics, Data Science, Mathematics, or a related quantitative field.
Familiarity with concepts around product safety and reliability, and Safety Management Systems
Six Sigma Black Belt or similar process improvement certification.
Familiarity with cloud-based data architectures (AWS/Azure).

Responsibilities

Work in conjunction with the Director of Engineering Product Integrity to develop and execute a roadmap for data analytics within the engineering org, ensuring alignment with Pratt & Whitney’s 2026 innovation goals.
Drive strategy and execution for enhanced analytics for insight and action around product safety and reliability.
Serve as the Subject Matter Expert (SME) for Design of Experiments (DoE), Statistical Process Control (SPC), and Reliability Analysis.
Mentor and grow a high-performing team of statisticians and data scientists, fostering a culture of technical excellence and continuous learning.
Partner with Manufacturing, R&D, and Product teams to implement predictive modeling and root-cause analysis that reduces "time-to-market."
Establish standards for data integrity and statistical validation protocols across the engineering lifecycle.