Work Location Type:Hybrid

As a leading industrial distributor with operations primarily in North America, Japan and the United Kingdom, We Keep The World Working by serving more than 4.5 million customers worldwide with products delivered through innovative technology and deep customer relationships. With 2023 sales of $16.5 billion, we're dedicated to providing value for customers, fostering an engaging culture for team members and driving strong financial results.

Our welcoming workplace enables you to learn, grow and make a difference by keeping businesses running and their people safe. As a 2024 Glassdoor Best Place to Work and a Great Place to Work-Certified company, we're looking for passionate people to join our team as we continue leading the industry over our next 100 years.

Position Details:

Grainger Technology Group seeks an innovative Manager of Applied Machine Learning to build out new efforts supporting our advantaged data assets around customers and sellers. This role will work with product managers, engineers, ML scientists, and our data users to create scalable ML models that improve our ability to gain deep insight into our sellers, proactively notify us when data changes, and create insights for our sales teams to know how to be the most effective at selling to the ones who get it done.

You Will:

• Work with a team of product managers, data scientists, data engineers and architects to build targeted products that help customers solve and answer specific problems.

• Be hands on with code (Python, SQL) on cloud based ML technologies (Databricks, Snowflake) to explore data, design features, and build models.

• Design, build, train, and monitor predictive and anomaly detection models using primarily structured data to detect changes across Grainger's millions of customers.

• Build, test, and deploy customer-facing analytical and ML endpoints, APIs, and trigger-based models that are a mixture of business logic, model, and data.

• Work as the first ML Scientist in a future small team to build models to support our sellers through the development of proactive models that identify changes in customer behavior and recommend best actions for sellers on the basis of those changes.

• Collaborate with researchers, software developers, business leaders, and end data users to define product requirements and provide analytical support.

• Articulate concepts and generate visual representations of model performance.

You Have:

• Master's degree in a field such as Statistics, Applied Mathematics, Physics, Engineering, Computer Science, or Economics, or equivalent experience.

• Experience building, deploying, and maintaining production machine learning solutions with SQL andPython.

• Experience usingcloud based development and analytics tools including Databricks, Snowflake, and MLFlow to create new and novel machine learning pipelines.

• Ability to set and define model and project based metrics and outcomes, build systems to deliver on those outcomes, and communicate those outcomes to the rest of the organization.

• Experience working directly with engineering teams to spec out data pipelines and work with them to deploy those pipelines.

• Relevant work experience in an analytical role involving data extraction, analysis, and communication of findingsto project stakeholders (both technical and non-technical) and end users.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.

We are committed to fostering an inclusive, accessible environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment. With this in mind, should you need a reasonable accommodation during the application and selection process, please advise us so that we can provide appropriate assistance.