Data Scientist (Onsite)

Location: US-CT-EAST HARTFORD-M ~ 400 Main St ~ BLDG M

 Position Role Type: Onsite

 U.S. Citizen, U.S. Person, or Immigration Status Requirements: U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.

 Security Clearance Type: None/Not Required

 Security Clearance Status: Not Required At RTX, the world largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.   Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years. Join us and help shape the future of aerospace and defense.

We are looking for an experienced Data Scientist who can bridge the gap between advanced predictive modeling, business intelligence, and complex aviation MRO operations. In this role, you will lead the architecture of our BI applications, spearhead our machine learning initiatives, and build robust data standards for our jet engine overhaul workflows. You will turn complex operational metrics—ranging from material wear patterns to FAA compliance tracking—into clear, actionable insights that drive strategic decision-making across the organization.

Web & Business Analytics BI Architecture Leadership: Lead the design, implementation, and support of local business intelligence applications and underlying architecture. Standards & Governance: Develop organizational standards, policies, and procedures regarding the form, structure, and attributes of BI tools and reporting systems. Performance Optimization: Optimize BI tool performance by defining strategic data filtering and indexing strategies that maximize user utility and report speed. Quality Metrics & Testing: Create rigorous testing methodologies, validation criteria, and data/information quality metrics to ensure operational trust in our data. Technology Scouting: Research emerging BI and data technologies, building comprehensive business cases to support their adoption. Strategic Insights: Analyze data trends in shop operations and supply chain to generate insights, draw business conclusions, and directly support operational-level decision-making.   Data Science & Machine Learning Predictive Modeling: Lead the analysis, statistical modeling, and interpretative explanation of complex aerospace data to generate robust analytical and predictive results (e.g., component failure forecasting, turnaround time optimization). Analytical Standards: Establish standards, software protocols, and procedures for building predictive models and analytical pipelines. Data Pipeline Management: Discover, clean, extract, and leverage data from enterprise systems to maximize data system performance and analytical accuracy. Model Validation: Design end-to-end testing and validation frameworks, establishing strict quality metrics for predictive models. Operational Problem Solving: Execute targeted data analyses to solve critical engineering, overhaul, and shop floor bottlenecks.

You Must Have: Advanced degree and 3+ years of experience in Data Science, Advanced Business Analytics, Technology and Machine Learning, preferably within Manufacturing, Aerospace, supply chain, or an FAA-regulated environment; OR Bachelor’s degree and 5+ years of relevant industry experience.

We Prefer: Advanced degree in Data Science, Computer Science, Statistics, Analytics, Engineering,