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Senior Engineer- Data Science at The Home Depot (Austin, TX)


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Location: Austin TX

Company Name: The Home Depot

Occupational Category: 15-1132.00,Software Developers, Applications

Date Posted: 2020-02-20

Valid Through: 2020-03-21

Employment Type: FULL_TIME

Description:

The Senior Engineer – Data Scientist will develop the analytical infrastructure and computational capabilities that drive decision making and impact the bottom line performance of internal applications at Home Depot. By partnering with business leaders and leveraging company and industry data, this role will develop predictive systems and algorithms for identifying trends and driving business solutions. This position’s primary focus is to manipulate large data sets to extract meaningful business information using statistics and machine learning techniques.

Preferred Qualifications:
• 3-5 years of experience in data mining and statistical analysis
• Previous work experience in eCommerce
• Experience with large-scale data analysis and a demonstrated ability to identify key
• Insights from data to solve business problems
• Strong problem solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• We’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc