Data Scientist

As a global manufacturer of complex aircraft engine components, Pursuit Aerospace is founded on a commitment to relentless, continuous, operational improvement and extraordinary customer service. We pride ourselves on competitive cost structure, exceptional on-time delivery, and industry-leading quality.

Pursuit Aerospace cultivates long-term relationships with our customers around the world through respect, teamwork, technology, and trust. We are driven to develop industry leading process innovations and manufacturing techniques on behalf of our customers.

The Data Scientist will support the development of data, analytics, and AI solutions for SIOP (Sales, Inventory, Operations Planning) transformation and help deliver measurable business impact on inventory and customer service. Working with senior team members and business partners, the Data Scientist will help frame supply chain problems, prepare and analyze operational data, develop and evaluate models, and translate results into dashboards, analytical tools, and decision-ready insights.

This role is designed for an early-career data scientist who is eager to build strong technical and business skills while contributing to practical solutions in a complex manufacturing environment.

Remote in the U.S., and travel 10-20%.

• 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.
• Collaborate with Product, Engineering, Operations, Supply Chain, and business stakeholders to understand business requirements and translate them into practical analytical work.
• Support high-impact analytics by helping scope business questions and develop solutions that improve metrics such as inventory, on-time delivery, and cost.
• Contribute to data products including analytical datasets, Snowflake tables, forecasting and time-series models, inventory and clear-to-build analytics, dashboards, and AI-powered tools.
• Help maintain…