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

Benefits

Annual base salary range: $95000-$125000
Bonus target range: 20%-25%
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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI/ML model developmentdata explorationfeature engineeringmodel tuningneural networksreinforcement learningnatural language processingPythonRSQL

Soft Skills

problem-solvinganalytical skillscommunication skillscollaborationstorytelling