Lead Data Scientist

Pursuit Aerospace•Prescott, AZ

10d•$144,000 - $198,000•Remote

About The Position

The lead 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 lead 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 owning 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.

Requirements

Bachelor’s degree required
2+ years in a data science role demonstrating solving complex business problems and independently building robust solutions that improve outcomes
2+ years in SQL, Python, Machine learning modeling, and time-series analytics
Must be authorized to work in the U.S. on a full-time basis without sponsorship now or in the future. The Company cannot offer employment to visa holders who require employer sponsorship in the future or cannot work now on a full-time basis.
Must be able to perform work subject to ITAR/EAR regulations.

Nice To Haves

Bachelor’s degree in data science or related field preferred
Master’s degree preferred
Proficient in SQL, Python, ML modeling, and time-series analytics; hands-on with Claude for AI-assisted coding against Snowflake tables, pipeline orchestration, GitHub for CI/CD, Azure data platform
Effective AI-assisted product development and proficient in using AI to plan, build, and quality-check code, and can critically evaluate, debug, and improve what it generates
Supply chain analytics knowledge such as demand forecasting, demand sensing, inventory management and clear-to-build reporting
Aerospace and/or manufacturing experience
Familiarity with ERP systems and hands-on experience with purchase order, production order, and inventory data

Responsibilities

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 and iterate quickly based on business feedback including data pipeline and snowflake tables, forecasting and time-series models, inventory and clear-to-build analytics, dashboards, and AI-powered tools.
Run analytics assets in production: keep all assets accurate and reliable and manage analytics operations leveraging technology
Engineer trustworthy data: turn large, messy operational data into well-structured, trusted datasets, and develop continuous improvement framework to enhance data quality and integrity
Drive decisions and adoption: translate analytical results and tools into clear, decision-ready recommendations and drive adoption across the business