Senior 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 senior data scientist will build data, analytics, and AI solutions to support SIOP (Sales, Inventory, Operations Planning) transformation and delivery business impact on inventory and customer service. The senior data scientist will function like a forward-deployed engineer who takes a supply chain problem from ambiguity to financial impact: framing the problem, shaping the data and models, building and iterating fast, and owing the solution end to end.

This role will work shoulder-to-shoulder with the business, move at its pace, and turn large, messy operational data into robust models, dashboards, and AI-powered tools that change decisions and outcomes.

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

• Develop and produce machine learning, statistical, forecasting, and time-series models that solve complex operational and business problems.
• Build solutions supporting key business areas including inventory optimization, demand forecasting, clear-to-build analytics, on-time delivery, production planning, operational efficiency, and cost reduction.
• Perform exploratory analysis, feature engineering, model selection, validation, optimization, deployment, and ongoing performance monitoring.
• Develop predictive and prescriptive analytical solutions that translate large and complex datasets into measurable business outcomes.
• Develop AI-powered applications and tools, including Generative AI and Large Language Model solutions where they provide measurable business value.

• Independently build end-to-end data science products, from business problem definition and data preparation through modeling, application development, deployment, and adoption.
• Develop robust analytical datasets and transformation workflows using Python and SQL to support machine learning and advanced analytics.
• Work with large, complex datasets across multiple enterprise systems and independently identify, clean, transform, and integrate the data required for analytical solutions.
• Develop dashboards, analytical applications, APIs, or decision-support tools that enable business users to consume model outputs and analytical insights.
• Build production-quality solutions with appropriate testing, version control, monitoring, documentation, and maintainability.

• Leverage modern cloud and data technologies such as AWS, Snowflake, Spark, S3, and related services to develop scalable analytical and machine learning solutions.
• Understand modern data architecture concepts including data lakes, ETL/ELT, streaming data, APIs, and cloud-native data platforms sufficiently to design data science solutions that integrate effectively with enterprise platforms.
• Collaborate with Product, Engineering, Operations, Supply Chain, and business stakeholders to translate business capabilities and requirements into practical analytical solutions.
• Deliver high-impact analytics: partner with cross-functional leaders to scope the problems and ship solutions that move real metrics: inventory, on-time delivery, and cost.
• Build end-to-end products: build products independently…