Sr Data Scientist

About the role

Grainger is a leading broad line distributor with operations primarily in North America and Japan. We serve more than 4.6 million customers worldwide with MRO products and value-added solutions. This role is located hybrid (2 days per week) from either our Lake Forest, IL or downtown Chicago office.

Responsibilities

• Analyze data sets, build predictive models, leverage operations research, and deploy and operationalize solutions to enhance supply chain performance.
• Apply operations research techniques such as linear programming, integer programming, and machine learning techniques such as classification, clustering, regression, and time series forecasting to build explanatory, predictive, and prescriptive models.
• Create and present materials necessary to communicate the results of analytical work and associated recommendations.
• Manipulate high-volume, high-dimensionality data from multiple sources, visualize patterns, anomalies, relationships, and trends, and perform feature engineering and selection.
• Create the code to support large-scale data analyses, model development, model validation and deployment.
• Aid junior team members in developing new skills and knowledge.

Requirements

• Bachelor's Degree BS in technical field such as Statistics, Mathematics, Data Science, Applied Analytics, Operations Research, Applied Science or Engineering required.
• Advanced degree (Master's Degree MS or PhD) in technical field such as Statistics, Mathematics, Data Science, Applied Analytics, Operations Research, Applied Science or Engineering preferred.
• 3+ years experience in analytics and data science roles required.
• Proficient in usage of databases (e.g. Teradata, Snowflake, Oracle) and querying languages (e.g. SQL).
• Knowledge of one or more of the following programming languages: Python, R, SPSS, or SAS.
• Proficiency with extraction and manipulation of very large structured and unstructured datasets.
• Proficiency with data visualization techniques.
• Proficiency with multi-variate linear regression, logistic regression, and time series modeling.
• Proficiency with statistical design of experiments, outlier detection methods, and statistical hypothesis testing.
• Proficiency with clustering and dimension reduction techniques.
• Knowledge of classification, gradient-boosting, and natural language processing algorithms.
• Experience leveraging cloud-based machine learning resources such as those from AWS.

Qualifications

• Demonstrated ability to translate analytical work into presentations (e.g. PowerPoint) suitable for non-technical audiences.
• Demonstrated ability to collaborate with business partners and colleagues.

Skills

• Intellectually curious, continuously learning, and motivated to explore new technologies, business insights, and customer behaviors.
• Strong commitment to innovation and long-term value creation through data-driven decision-making.

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.

Pay

The anticipated base pay compensation range for this position is $103,600.00 – $172,600.00. This role is eligible for an incentive target of up to 10 %, based on the achievement of individual and company performance objectives in accordance with the current terms of the incentive program which are subject to change.

Schedule

This role is to be located hybrid (2 days per week) from either our Lake Forest, IL or downtown Chicago office is preferred. Remote/virtual may be considered for candidates outside this area.