Applied Machine Learning Scientist
Role Overview
The Machine Learning Team in Grainger Technology Group is hiring an Applied ML Scientist.
The role focuses on designing, developing, and deploying machine learning solutions for Grainger's e-procurement system.
Solutions may use classical statistical modeling, modern AI, and foundation models to streamline e-procurement operations.
Key Skills for This Role
Full Job Posting
Work Location Type
- Hybrid work arrangement.
Compensation
- Anticipated base pay compensation range is $112,900 to $188,100.
- The role is eligible for an incentive target of up to 5% based on individual and company performance objectives.
Position Details
The Machine Learning Team in Grainger Technology Group is hiring an Applied ML Scientist.
The role focuses on designing, developing, and deploying machine learning solutions for Grainger's e-procurement system.
Solutions may use classical statistical modeling, modern AI, and foundation models to streamline e-procurement operations.
You Will
- Conduct exploratory data analysis to frame business problems and define data and modeling requirements.
- Design, train, validate, and improve models for prediction, classification, ranking, retrieval, recommendation, matching, and product data enrichment.
- Build reusable Python, SQL, and data workflows for experimentation, model development, and deployment.
- Evaluate model performance through metrics, experiments, and error analysis.
- Collaborate with engineers, product managers, analysts, and stakeholders on scalable production-ready solutions.
- Support agentic automation, digital assistants, document intelligence, and entity resolution use cases.
- Document methods and communicate technical findings to technical and nontechnical audiences.
You Have
- Bachelor's degree in a relevant field is required.
- At least 2 years of experience in machine learning, data science, applied statistics, or a related analytical field is required.
- Strong Python and SQL programming skills are required.
- Knowledge of machine learning, statistical modeling, and model evaluation techniques is required.
- Experience with feature engineering, experimentation, and model performance interpretation is required.
- Experience with maintainable code, version control, and code review is required.
- A related master's degree is preferred.
- Experience with Python API frameworks, workflow orchestration, Snowflake or Databricks, MLflow, Docker, and Kubernetes is preferred.
Rewards and Benefits
- Benefits include medical, dental, vision, and life insurance coverage starting on day one.
- Full-time employees receive 18 paid time off days annually, prorated based on start date, and six company holidays.
- The company contributes 6% to a 401(k) retirement savings plan each pay period without requiring an employee contribution.
- Benefits also include employee discounts, tuition reimbursement, financial counseling, and parental support programs.
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