Data Scientist Specialist - Customer Service

Job Description
- Data Scientist Specialist
- Customer Service (344102)

Data Scientist Specialist
- Customer Service (344102)

Textron Aviation has been inspiring the journey of flight for nine decades through the iconic and beloved Cessna and Beechcraft brands. We are passionate advocates of aviation, empowering people with the freedom of flight. As you join our legacy as a global leader in private aviation, you’ll have opportunities to try new fields, expand your skills and knowledge, stretch your abilities, and build your career.

We provide a competitive and extensive total rewards package that includes pay and innovative benefits to support you and your family members – now and in the future, beginning day one. Your success is our success.

Data Scientists drive strategic initiatives by performing advanced analytics, predictive modeling, and machine learning on complex internal and external datasets. Theyleverageadvanced mathematics, statistics, and code-first toolsto 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.

• Support data exploration, hypothesis testing, and foundational predictive analytics.
• Independently develop machine learning models for classification, regression, clustering, and time-series analysisusing 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, includingaircraftOEM 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.
• Lead development of predictive models and advanced analytics workflows.
• Mentor junior data scientists and contribute to team knowledge sharing.
• Design experiments and causal inference studies to support strategic initiatives.
• Collaborate with cross-functional teams to integrate models into business processes.
• Champion adherence to governance frameworks and global data science standards.
• Drive innovation in datasciencemethodologies and tools.
• Influence enterprise-wide strategy through advanced modeling and simulation.
• Lead cross-domain projects involving deep learning, NLP, or advanced time-series forecasting.
• Advocate for ethical AI practices and model interpretability.
• Serve as a thought leader in data science governance, ensuring consistency and quality across teams.

• Bachelor’s degree required in Applied Mathematics, Statistics, Computer Science,Data Science,or related technical field/coursework.
• Minimum 7 years of relevant experience required in data science, machine learning, artificial intelligence, predictive modeling, or advanced analytics.
• Master’s or PhD degreein
  
  Applied Mathematics, Statistics, Computer Science, Data Science, or related field preferred.
• Aviation experience preferred.

• Excellent written and verbal communication skills with the ability to explain complex technical concepts and analytical findings to both technical and non-technical audiences.
• Practical application experience with Python (and associated libraries: pandas, scikit-learn,etc.), SQL, and statistical analysis.
• Experience with data visualization tools (Matplotlib,Seaborn,Plotly,or similar).
• Advancedproficiencywith tree-based algorithms and dimensionality reduction.
• Experience working with relational databases and developing complex data sets.
• Experience with generative AI concepts, including large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and comfortable withAIcoding assistants.
• Experience building, deploying, and managing machine learning solutions using cloud-native platforms (Azure ML,MLflow, AWS Sage Maker, etc.),…