Sr. Data Scientist

Lennox (NYSE: LII) Driven by 130 years of legacy, HVAC and refrigeration success, Lennox provides our residential and commercial customers with industry-leading climate-control solutions. At Lennox, we win as a team, aiming for excellence and delivering innovative, sustainable products and services. Our culture guides us and creates a workplace where all employees feel heard and welcomed. Lennox is a global community that values each team member’s contributions and offers a supportive environment for career development. Come, stay, and grow with us.

We are seeking a motivated and analytical Data Scientist to develop machine learning models and advanced analytics solutions that drive business value across the organization. In this role, you'll partner with cross-functional teams to solve complex business problems, uncover actionable insights, and transform data into scalable, data-driven solutions. The ideal candidate has a strong foundation in statistics, machine learning, and programming, along with a passion for solving real-world challenges through data. If you enjoy working with large, complex datasets and collaborating to deliver innovative solutions, we'd love to hear from you.

Machine Learning & Analytics

• Develop and deploy machine learning models and predictive analytics solutions.
• Build custom data models and algorithms to solve complex business problems.
• Apply statistical techniques and advanced analytics to generate actionable insights.
• Use data exploration techniques to identify trends and uncover new opportunities.

Business Partnership & Strategy

• Partner with stakeholders to understand business objectives and translate them into data-driven solutions.
• Identify opportunities for high-impact analytics initiatives that improve business performance.
• Develop expertise across Sales, Marketing, Engineering, Supply Chain, and Finance datasets.

Data Management & Collaboration

• Merge, manage, and analyze large, complex datasets.
• Collaborate with cross-functional teams to implement models and monitor data quality and model performance.
• Develop and improve analytics processes, workflows, and best practices.
• Present findings through clear data visualizations and communicate insights to technical and non-technical audiences.

Teamwork & Leadership

• Foster a collaborative team environment through knowledge sharing and mentoring.

• Support continuous improvement initiatives and promote best practices.

• Build strong working relationships across the organization.

• Bachelor’s degree in computer science, Data Science, Analytics, Statistics, Business, Information Science, or a related field with 5+ years of experience in data science, analytics, machine learning, or a related discipline; or a Master’s degree in a related field with 3+ years of relevant experience.

• Strong problem-solving skills with the ability to apply quantitative and qualitative analytical methods.

• Proficiency in Python, R, SQL, PySpark, or similar programming languages used for data analysis.

• Knowledge of machine learning techniques, including clustering, decision trees, random forests, logistic regression, linear regression, gradient boosted trees, and naïve Bayes classifiers.

• Understanding of big data architectures, distributed computing concepts, and large-scale data processing.

• Experience working with relational databases and large, complex datasets.

• Strong communication skills with the ability to present analytical findings to technical and non-technical stakeholders.

• Experience with Spark MLlib and strong software development skills.

• Basic understanding of unstructured data analysis.

• Experience with data visualization tools such as Tableau, Power BI, or Qlik.

Preferred Qualifications

• Exposure to deep learning techniques.
• Experience with distributed deep learning frameworks such as TensorFlow, Horovod, or similar technologies.