JOB SUMMARY:

Data Scientists drive strategic initiatives by performing advanced analytics, predictive modeling, and machine learning on complex internal and external datasets. They leverage advanced mathematics, statistics, and code-first tools to deliver high-impact, actionable insights. Unlike Data Analysts, Data Scientists focus on building and validating models, conducting experiments, and generating recommendations that directly inform business strategy and operational transformation. 

We are seeking an experienced Data Scientist to join our small, specialized, and highly motivated team that is implementing predictive maintenance and connected aircraft solutions for a large fleet of Textron Aviation aircraft. In this senior position, you will merge large scale time-series aircraft sensor data, parts, and maintenance records using a variety of machine learning, deep learning, AI, and visualization methods. You will keenly focus on maximizing the operational availability of customer jet, turboprop, and piston aircraft along with efficient aircraft maintenance practices. As a key part of your role, you will mentor and provide technical leadership to junior data scientists, foster creativity, and champion innovative, cutting-edge data science methodologies across the organization.

At Textron Aviation, we are building a community of Data & Analytics professionals with an emphasis on collaboration and cross functional support. You will have the opportunity to work closely with your peers throughout the organization toward a vision of data driven strategy. 

JOB RESPONSIBILITIES:

·        Support data exploration, hypothesis testing, and foundational predictive analytics.  

·        Independently develop machine learning models for classification, regression, clustering, and time-series analysis using Python and relevant libraries. 

·        Collaborate with analysts and engineers to prepare and clean data for modeling.  

·        Document methodologies and contribute to reproducible research practices.  

·        Develop foundational understanding of the business domain, including aircraft OEM operations. 

·        Apply advanced statistical techniques to evaluate model performance and business impact.  

·        Work with large datasets using Python, SQL, and cloud-native platforms.  

·        Communicate findings through technical documentation and stakeholder presentations.  

·        Contribute to the development of analytics best practices and model governance.