AI Data Scientist

Role Overview

• Design, develop, and deploy advanced AI/ML models and algorithms that improve operational efficiency, forecasting accuracy, and decision intelligence across the Hunter Douglas supply chain
• Conduct data exploration, feature engineering, and model tuning to ensure accuracy, robustness, and business applicability
• Collaborate with business stakeholders to translate complex challenges into data-driven solutions aligned with organizational goals
• Monitor, retrain, and optimize models post-deployment to maintain high performance as data and business conditions evolve
• Apply state-of-the-art methods such as neural networks, reinforcement learning, natural language processing (NLP), and generative AI to tackle diverse business challenges
• Contribute to the AI strategy roadmap, ensuring alignment with Hunter Douglas’s digital transformation initiatives
• Work with data engineers and IT to ensure efficient data pipelines, scalable infrastructure, and model deployment
• Partner with internal and external technical teams, vendors, and consultants to implement and scale AI solutions
• Communicate findings and insights clearly to both technical and non-technical stakeholders through visualizations, presentations, and storytelling
• Stay at the forefront of AI and analytics innovation, evaluating new tools, methodologies, and technologies for potential adoption
• Collaborate with digital product and IT teams to develop and integrate AI-assisted tools and automations within Hunter Douglas’s VIBE platform and data ecosystem
• Experiment with AI coding assistants (e.g., Cursor, GitHub Copilot, OpenAI Codex) to accelerate analytics and model development and improve reproducibility
• Support the creation of custom AI copilots and prompt libraries for use in digital supply chain tools, analytics dashboards, and planning applications
• Partner with the Digital Supply Chain Leader to prototype intelligent process automation for recurring planning, logistics, quality, or operational workflows.

Requirements

• Bachelor’s degree in a quantitative field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics, Operations Research, or related)
• 5+ years of experience in AI/ML model development, deployment, and performance optimization in a business or industrial context
• Strong proficiency in Python, R, or SQL for data science and model development
• Demonstrated experience with machine learning frameworks and cloud platforms (AWS, Azure, GCP)
• Proven ability to design and operationalize data science solutions in real-world environments
• Experience with predictive modeling, optimization, and time-series forecasting, ideally within supply chain, operations, or commercial analytics
• Knowledge of data visualization and BI tools (Power BI, Tableau, or similar)
• Strong problem-solving, analytical, and communication skills
• Familiarity with version control (Git) and collaborative development practices.

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• Python
• SQL
• Tableau

Benefits

• Generous benefits package including medical, dental, vision, life, disability
• A company culture that prioritizes internal development and professional growth
• Time off with pay
• 401(k) plan with a degree of employer matching
• Paid parental leave
• Wellness programs and product discounts