AI Analytics Engineer Job

Armstrong World Industries is a leader in innovative architectural applications, and they are seeking an AI Analytics Engineer to leverage AI technologies for actionable insights from complex business data. The role involves designing and deploying predictive models to enhance sales strategies and improve revenue growth.

Responsibilities:

• Integrate and transform complex data from CRM systems, internal databases, construction documents, project plans, and geospatial sources into reliable, analytics-ready datasets
• Evaluate data for completeness, reliability, and bias to ensure high-quality, responsible AI and modeling outcomes
• Develop and deploy predictive models that improve sales effectiveness, deal performance, and revenue growth
• Extract insights from structured and unstructured data, including technical documents and geographic information, to identify key drivers of margins and competitive positioning
• Apply AI-assisted development tools to accelerate solution delivery while maintaining high standards of accuracy, transparency, and documentation

Requirements:

• Degree in Statistics, Computer Science, Economics, Data Science or related quantitative field or 5+ years of equivalent work experience
• High School Diploma/GED
• 2 years of AI/ML experience
• Proficiency in Python or comparable programming experience
• Working knowledge of databases (SQL)
• Source control (Git)
• Strong foundation in statistics and model evaluation, including logistic regression, hypothesis testing, experimental design, and classification metrics (e.g., precision, recall, AUC, calibration)
• Analytical mindset with intellectual curiosity and comfort navigating ambiguity in data quality, definitions, and requirements
• Experience using AI-assisted development tools (e.g., Claude Code, Codex, or similar)
• Ability to clearly communicate technical findings to non-technical stakeholders
• Please include a link to your GitHub or other code repository showcasing relevant work
• Experience with feature engineering, data pipelines, and diverse data types (text, images, geographic, etc.)
• Experience applying machine learning and model evaluation, with familiarity in sales pipeline dynamics, CRM data, and pricing/margin analysis
• Clear communicator who translates statistical insights into actionable business implications
• Willing to invest in understanding the business context behind the data