Data Scientist III

Lennox International • Richardson, TX

3d • Onsite

About The Position

Lennox (NYSE: LII) is a company with a 130-year legacy in HVAC and refrigeration, providing industry-leading climate-control solutions. They aim for excellence and deliver innovative, sustainable products and services. Lennox fosters a culture where employees feel heard and welcomed, valuing contributions and offering a supportive environment for career development. This role involves executing complex data-science initiatives, developing advanced machine-learning models, designing scalable analytics solutions, and generating deep insights from large and varied datasets. The position requires developing expertise in business functions, translating needs into advisory solutions, identifying high-ROI opportunities, and refining data management and analytics procedures. The Data Scientist III will develop and deliver end-to-end machine-learning projects, apply data-exploration techniques, build custom models, and analyze large structured and unstructured datasets across sales, marketing, engineering, supply chain, and finance. Collaboration with cross-functional teams for production implementation, model performance monitoring, and fostering pragmatic analytics are key. The role also involves assessing analytical tools, supporting proof-of-concepts, and presenting insights through data visualization. A senior-level contribution is expected through organization, coaching, mentorship, and championing learning initiatives.

Requirements

• Master’s or foreign equivalent degree in Computer Science, Data Science, Business Analytics, Electrical and Computer Engineering, Mathematics, Information Systems, Management Science, Information Technology Management, or a related field.
• 2 years of experience in the job offered, or as a Data Engineer, Data Analyst, or in a related/similar position.
• 2 years with Python, R, Scala, or SQL.
• 2 years with Database technologies including Build ETL/ELT pipelines, SQL scripting within data Warehouses, and Build analytical data models.
• 2 years applying machine-learning algorithms including regression, tree-based methods, clustering, or neural network models.
• 2 years translating business challenges into visual analyses using Qlik, Tableau, Power BI, or comparable reporting tools.
• Completion of a university-level course, research project, thesis, internship or one year of work experience involving Business Analytics, Management Systems and Processes, Statistics and Machine Learning, and Advanced Analytics.

Responsibilities

• Execute complex data-science initiatives across multiple business domains.
• Develop advanced machine-learning models.
• Design scalable analytics solutions.
• Generate deep insights from large and varied datasets.
• Develop deep expertise in business functions and translate needs into high-value advisory solutions for stakeholders.
• Identify high-ROI opportunities and refine data-management and analytics procedures, systems, workflows, and best practices to strengthen the machine-learning practice.
• Develop and deliver end-to-end machine-learning projects.
• Apply data-exploration techniques to surface novel questions.
• Build custom models, algorithms, and analytical frameworks that improve decision-making, operational efficiency, and ROI.
• Merge, manage, interrogate, and analyze large structured and unstructured datasets.
• Become expert in sales, marketing, engineering, supply chain, and finance data.
• Apply statistical techniques and modern ML methods to produce solutions to complex problems.
• Collaborate with cross-functional teams to implement models in production.
• Develop tools to monitor model performance, drift, and data accuracy.
• Foster pragmatic analytics combining advanced methods, new technologies, and deep business insight to drive decisions.
• Assess analytical tools, technologies, and external data sources.
• Support proof-of-concepts to accelerate business success and sustained growth.
• Present insights using clear, compelling data-visualization techniques.
• Demonstrate senior-level contribution through organization, coaching, and mentorship.
• Share information openly, coordinate activities, and jointly solve problems.
• Support team education on new processes and technologies.
• Model effective cross-functional communication and champion learning initiatives.
• Cultivate positive working relationships across the organization.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior