Senior Applied Machine Learning Scientist

Grainger Businesses • Lake Forest, IL

55d • Remote

About The Position

As a Senior Machine Learning Scientist, you will lead the design, development, and deployment of scalable ML solutions that directly influence strategic business decisions and product capabilities. You’ll work end-to-end — from understanding complex business challenges and exploring data, to developing, deploying, and operationalizing advanced models that make a real-world impact. Our team is dedicated to leveraging data, advanced analytics, and machine learning to deliver tangible, long-term business value and measurable financial impact.

Requirements

• MS degree or PhD in a technical field such as Mathematics, Data Science, Applied Analytics, Operations Research, Computer Science, Applied Science or Engineering
• 3+ years of experience delivering end-to-end ML solutions at scale — from data ingestion through model deployment and monitoring
• Advanced proficiency in Python and SQL for data manipulation and model development
• Hands-on experience with machine learning frameworks and deployment tools (e.g., scikit-learn, PyTorch, TensorFlow, MLflow, REST APIs)
• Familiarity with containerization, CI/CD, and version control (Kubernetes, Docker, Git)
• Experience building interactive, model-driven applications using React, Streamlit, or similar frameworks
• Experience with databases (Teradata, Snowflake, S3) and data processing at scale
• Proven ability to apply deep learning and transformer-based modeling methods in production environments
• Familiarity with modern ML architectures, including embedding models, multimodal systems, or generative AI (LLMs, diffusion models) where applicable.
• Strong analytical and problem-solving mindset; able to translate complex business challenges into structured, data-driven solutions
• Excellent communication skills, with the ability to convey technical concepts to both technical and business audiences

Responsibilities

• Partner with business teams to understand problems, identify opportunities, and translate them into impactful ML solutions.
• Manipulate high-volume, high-dimensionality data from multiple sources, visualize patterns, anomalies, relationships, and trends, and perform feature engineering and selection
• Design, build, and deploy scalable ML models and pipelines from ideation to production, following best practices in MLOps and software engineering.
• Use advanced ML methods — including deep learning, NLP, LLMs, and time series forecasting — and selectively apply optimization approaches like linear programming or simulation to build scalable, data-driven solutions.
• Develop interactive analytical tools and applications (e.g., React, Streamlit) to visualize model outputs, simulate scenarios, and make insights actionable.
• Design and deploy scalable, automated ML workflows for data analysis, model development, validation, and deployment — integrating analytical products and APIs into business systems.
• Collaborate with business partners, engineering, MLOps/DevOps and Product teams to design and implement AI solutions that integrate predictive and prescriptive components
• Articulate concepts and generate visual representations of your work and the impact it creates — communicating analytical insights clearly to technical and non-technical audiences
• Stay current with advancements in machine learning, optimization, simulation, and decision science, applying relevant innovations to your work.

Benefits

• Medical, dental, vision, and life insurance plans with coverage starting on day one of employment and 6 free sessions each year with a licensed therapist to support your emotional wellbeing.
• 18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date) and 6 company holidays per year.
• 6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required.
• Employee discounts, tuition reimbursement, student loan refinancing and free access to financial counseling, education, and tools.
• Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 11-50 employees