Data Scientist enhancing merchandising and inventory performance using machine learning techniques at Nordstrom. Collaborating with teams to develop data - driven solutions for better customer experiences.
About the role
- Data Scientist leveraging machine learning and statistical analysis for business insights at Grainger. Driving value and growth through data-driven decisions and innovative solutions.
Responsibilities
- Work closely with the business to understand the problem space, identify the opportunities, and translate business problems into technical solutions using machine learning frameworks.
- Conduct exploratory data analysis and apply deep business knowledge to customer and marketplace data to uncover new business insights.
- Manipulate high-volume, high-dimensionality data from multiple sources, visualize patterns, anomalies, relationships, and trends, and perform feature engineering and selection.
- Design and conduct experiments, collect the data necessary to perform statistical hypothesis testing, and create inferences and recommendations.
- Create scalable, efficient, automated processes to support large scale data analyses, model development, model validation and deployment.
- Apply techniques such as classification, clustering, dimension reduction, regression, NLP, deep learning, time series forecasting to build explanatory, predictive, prescriptive models appropriate for solving different business problems.
- Create and present the materials necessary to effectively communicate the results of analytical work and associated recommendations.
- Develop expertise on Grainger's business operations, go-to-market model, and the broader Maintenance, Repair, and Operations (MRO) market.
Requirements
- Bachelor's Degree Data Science, Statistics, Mathematics, Computer Science, or other quantitative field.
- Master’s Degree Data Science, Statistics, Mathematics, Computer Science, or other quantitative field (Preferred).
- 2+ years experience in specialized research, such as informatics, data collection, scientific research and research equipment (Required).
- Proficiency in databases such as Teradata, Snowflake or Oracle and querying languages (e.g. SQL) (Experienced).
- Experienced with at least one data science programming languages (e.g., Python, R) and working with structured and unstructured datasets.
- Experience with machine learning techniques such as classification, clustering, dimension reduction, regression, NLP algorithms, and time series modeling.
- Experience with statistical design of experiments, outlier detection methods, and statistical hypothesis testing.
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.
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