Work Location Type: HybridReq Number 332078
CompensationThe 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.
Rewards and BenefitsWith benefits starting on day one, our programs provide choice and flexibility to meet team members' individual needs, including:
- 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.
For additional information and details regarding Grainger's benefits, please click on the link below:
https://experience100.ehr.com/grainger/Home/Tools-Resources/Key-Resources/New-Hire
Grainger BenefitsThe pay range provided above is not a guarantee of compensation. The range reflects the potential base pay for this role at the time of this posting based on the job grade for this position. Individual base pay compensation will depend, in part, on factors such as geographic work location and relevant experience and skills.
The anticipated compensation range described above is subject to change and the compensation ultimately paid may be higher or lower than the range described above.
Grainger reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion at any time, consistent with applicable law.
Position DetailsWe are looking for a Sr Data Scientist to join our Inventory Optimization team, bringing expertise in data analysis and advanced quantitative methods (machine learning and operations research) to drive impactful business outcomes. These analytics-based solutions are used to improve how Grainger's supply chain is designed, operated and maintained, aligning solutions with strategic goals and service to our customers. The ideal candidate is intellectually curious, continuously learning, and motivated to explore new technologies, business insights, and customer behaviors. This role requires a strong commitment to innovation and long-term value creation through data-driven decision-making.
This position 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.
You Will- 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 etc. and machine learning techniques such as classification, clustering, regression, and time series forecasting to build explanatory, predictive, and prescriptive models appropriate for solving different supply chain problems.
- Conduct exploratory data analysis and apply supply chain understanding to uncover new insights and form recommendations rooted in analytics.
- Create and present the materials necessary to communicate the results of analytical work and associated recommendations and influence the use of analytical recommendations.
- Use your experience on Grainger's business operations, go-to-market model, and the broader Maintenance, Repair, and Operations (MRO) market to inform analytical decisions and 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.
- Assist junior team members in developing new skills and knowledge.
You Have- 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
- 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
