Data Scientist

Pursuit Aerospace is a global manufacturer of complex aircraft engine components focused on continuous operational improvement, customer service, and advanced manufacturing techniques. The Data Scientist will support data, analytics, and AI solutions for SIOP transformation by preparing operational data, developing models, and creating dashboards and decision-ready insights for supply chain and manufacturing stakeholders.

What you'll do:

• Develop machine learning, statistical, forecasting, and time-series models with guidance from senior team members
• Support analytical solutions for key business areas including inventory optimization, demand forecasting, clear-to-build analytics, on-time delivery, production planning, operational efficiency, and cost reduction
• Perform exploratory data analysis, data cleaning, feature engineering, model development, validation, and performance evaluation
• Analyze operational datasets and translate findings into clear insights and recommendations for business stakeholders
• Support the development of AI-powered applications and tools, including Generative AI and Large Language Model solutions where they provide measurable business value
• Contribute to end-to-end data science projects, from business problem definition and data preparation through modeling, testing, visualization, and deployment, with guidance from senior team members
• Develop and maintain analytical datasets and data transformation workflows using Python and SQL to support machine learning and advanced analytics
• Work with data from multiple enterprise systems to identify, clean, transform, validate, and integrate data required for analytical solutions
• Develop dashboards, analytical applications, or decision-support tools that help business users consume model outputs and analytical insights
• Follow team standards for testing, version control, documentation, monitoring, and maintainable analytical code
• Use modern cloud and data technologies such as Snowflake, AWS, Azure, Spark, S3, or related services to support analytical and machine learning solutions
• Build working knowledge of modern data architecture concepts including data lakes, ETL/ELT, APIs, and cloud-native data platforms

What they're looking for:

• Bachelor's degree
• 1+ years of experience in data science, analytics, engineering, or a related quantitative role using SQL and/or Python for data analysis, data preparation, or analytical solution development. Relevant internships, co-ops, or research experience may be considered
• Must be authorized to work in the U.S. on a full-time basis without sponsorship now or in the future
• Must be able to perform work subject to ITAR/EAR regulations
• Bachelor's degree in data science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
• Master's degree in a quantitative or technical field
• Experience developing or evaluating at least one machine learning, statistical, forecasting, or time-series model through work, internships, research, or academic projects
• Working knowledge of SQL and Python and familiarity with machine learning, statistical modeling, or time-series analytics
• Exposure to Snowflake, AWS, Azure, GCP, Spark, data pipelines, Git/GitHub, CI/CD, or other modern data and cloud technologies
• Experience through coursework, internships, research, or projects developing machine learning, statistical, or forecasting models and evaluating model performance
• Experience working with real-world or imperfect datasets, including data exploration, cleaning, transformation, feature engineering, and data-quality checks
• Familiarity with data models, ETL/ELT concepts, or cloud data environments such as Snowflake, AWS, Azure, or GCP

Benefits:

• Health and disability insurance
• 401(k) match
• Flexible spending accounts
• EAP
• Paid time off
• Company-paid holidays
• The specific programs and options available to an employee may vary depending on date of hire, schedule type, and the applicability of collective bargaining agreements, among other things.