Sr. Data Scientist

HNI Corporation is a global family of brands for the workplace and home dedicated to enhancing the spaces where we live, work, and gather. We pride ourselves on fostering an environment where we make a positive impact on others; upholding our beliefs in integrity, inclusion and belonging. The Senior Data Scientist is a highly experienced individual contributor within the Decision Science team, responsible for solving complex, cross-functional, and high-impact business problems using advanced analytics, machine learning, and statistical modeling. This role goes beyond model development to include technical leadership, solution design, and end-to-end ownership of data science initiatives—from problem framing and data strategy through production deployment and performance monitoring. As a senior member of the team, this role helps shape HNI’s data science standards, mentors other data scientists, and partners closely with business and IT leaders to ensure data science solutions are scalable, reliable, and aligned to strategic priorities. WORK AUTHORIZATION & LOCATION REQUIREMENT This position is primarily remote but requires candidates to reside within the Chicagoland area and attend occasional onsite meetings as needed. Due to the remote nature of this role and associated employment requirements, the company is unable to provide employment-based visa sponsorship now or in the future. Applicants must be authorized to work in the United States without sponsorship, and candidates requiring current or future sponsorship will not be considered.ESSENTIAL DUTIES AND REPONSIBILITIESAdvanced Analytics & Model Development

• Lead the design, development, and deployment of advanced predictive, prescriptive, and machine learning models to support enterprise decision-making.
• Apply advanced statistical techniques, feature engineering, and algorithm selection to complex, multi-source datasets.
• Use SQL, Python and related tools to analyze large-scale internal and external data sources.
• Identify patterns, trends, and drivers of business performance across manufacturing, supply chain, sales, and operations.

End-to-End Solution Ownership

• Own data science solutions from initial concept and feasibility assessment through production deployment and ongoing optimization.
• Define modeling approaches, validation strategies, and performance metrics to ensure business value and technical rigor.
• Monitor deployed models for performance, drift, and stability; recommend enhancements or retraining strategies.
• Partner with data engineering and IT teams to ensure models are production-ready and operationally supported.

Business Partnership & Communication

• Translate complex analytical concepts and results into clear, actionable insights for business leaders and non-technical stakeholders.
• Act as a trusted analytics advisor to cross-functional partners, influencing decisions through data-driven recommendations.
• Support executive-level discussions by framing trade-offs, assumptions, and risks associated with analytical solutions.

Technical Leadership & Standards

• Establish and promote best practices for model development, documentation, testing, and deployment.
• Mentor and guide junior and mid-level data scientists, providing technical feedback and coaching.
• Contribute to the evolution of HNI’s data science toolset, methodologies, and operating model.
• Evaluate emerging analytics, ML, and AI techniques and recommend practical adoption.

Data Strategy & Innovation

• Collaborate on the design of data collection strategies, analytics pipelines, and feature stores that improve modeling effectiveness.
• Partner with analytics, BI, and data platform teams to ensure data science outputs are usable across the enterprise.
• Support advanced use cases such as optimization, simulation, and early-stage AI initiatives.

EXPERIENCE AND REQUIRED SKILLS

• 7+ years of progressive experience in advanced analytics, data science, or machine learning roles.
• Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline.
• Demonstrated success delivering end-to-end data science solutions in a production environment.