Senior Data Scientist - 333116
$103,600–$172,600 year
HybridLake Forest, Illinois, United States
Job Summary
Build and execute complex queries to pull data from SQL databases and create Python scripts to identify patterns and trends. Perform exploratory and statistical analysis to generate insights for management teams, create predictive models to improve operational efficiency, and build dashboards in visualization tools to support ad-hoc data requests. Use natural language processing to summarize notes and gain insight into hidden trends while leveraging cloud-based machine learning resources. Demonstrate the ability to translate analytical work into presentations suitable for non-technical audiences and collaborate with business partners. This role supports the High-Tech Solutions segment of W.W. Grainger, Inc., offering up to 70% remote work.
Required Qualifications
- Bachelor's degree in Statistics, Mathematics, Data Science, Applied Analytics, Operations Research, Applied Science or Engineering or related field
- 3 years of related experience
- Must live within normal commuting distance of the worksite
- Up to 70% remote work allowed
Desired Qualifications
- Will accept any level of experience in the following skills: Build and execute complex queries to pull data from SQL databases
- Create python scripts to identify patterns, trends and relationships within the data
- Perform exploratory and statistical analysis to generate insights for management teams
- Create predictive models to improve operational efficiency, enhance cost savings and reduced human error (Python, R, SPSS)
- Research alternative development methodologies and make recommendations for team improvement
- Build dashboards in visualization tools (Tableau) to support ad-hoc data requests and data analysis to monitor business health
- Use Natural Language processing to summarize notes and gain insight into hidden trends
- 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 clustering and dimension reduction techniques
- Knowledge of classification, gradient-boosting, and natural language processing algorithms
- Proficiency with statistical design of experiments, outlier detection methods, and statistical hypothesis testing
- Experience leveraging cloud-based machine learning resources such as those from AWS
- Proficiency with Machine Learning techniques like multi-variate linear regression, logistic regression, time series modeling, clustering and dimension reduction, classification, gradient-boosting
- 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
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