Sr. Data Scientist, Online - Full-time / Part-time

Position Purpose:

At HomeDepot.com, our award-winning e-Commerce team is blazing a trail of retail shopping innovation by leveraging cutting-edge technology with our 2,200+ store locations and a relentless focus on customer service. We have been named one of the world's most innovative companies and we are on a mission to provide the best interconnected shopping experience to our consumers. To do so, we need more dreamers, innovators and big thinkers passionate about re-imagining the future of retail. Interested in making history with us? If so, apply today to experience what it’s like to be a part of our HomeDepot.com team. Who knows? Your next big idea may just change the future of retail!

The Sr. Data Scientist will be responsible performing large-scale statistical analysis for identifying opportunities, evaluating existing gaps, and proposing scalable solutions. This role will lead model building, evaluation, and productionalization from end to end to strengthen Homedepot.com's recommendation, personalization and overall site experience. The Sr. Data Scientist will be expected to operate with minimal supervision and mentor data scientists to complete analytical tasks and productionalize model-driven solutions.

Major Tasks, Responsibilities, and Key Accountabilities:

• 40% - Perform Statistical analysis for identifying opportunities, evaluating existing gaps, and proposing scalable solutions. Design and develop algorithms and models to improve search and personalization; Establish scalable, efficient processes for large scale data analysis, model development and model implementation.
• 20% -Present findings in easily understood ways and focuses on how data analytics fits into the bigger picture.
• 20% -Communicate with product management, IT, and other business teams on problem definition and writing requirement documents for efficient model building and deployment.
• 10% -Mentor and develop the technical and business skills of Data Scientists.
• 10% -Define best practices and articulate a clear vision for how data analyses and model productionalization should be done.

Nature & Scope

• This position reports to Director, Data Science.
• No direct responsibility for supervising others

Environment:

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Travel:

• Typically requires overnight travel less than 10% of the time.

Minimum Qualifications:

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Education Required:

• The knowledge, skills and abilities typically acquired through the completion of a master's degree program or equivalent degree in a field of study related to the job.

Years of Relevant Work Experience: 5 years

Physical Requirements:

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Additional Qualifications:

• Strong data mining and machine learning background
• Experience with big data environment

Preferred Qualifications:

• PhD in Computer Science, Math or related quantitative field
• Experience with recommender systems, information retrieval, graph analysis, statistical modeling, neural network, and natural language processing
• Experience with large-scale data analysis and building high-performance computational software
• Experience with e-Commerce and analyzing clickstream data
• Experience with big data environment including Spark, Hadoop, Hive, etc.
• Proficiency in at least one statistics/data analysis package, such as Python or R
• Proficiency in at least one programming language, such as Java or Python, etc.
• Solid coding practices including good design documentation, unit testing, and integration testing
• Experience working with real-world noisy data

Knowledge, Skills, Abilities and Competencies:

• Strong communication and data presentation skills; ability to communicate with data-driven stories

• Ability to quickly adapt to new technologies, tools and techniques
• Flexible and responsive; able to perform in a fast paced, dynamic work environment and meet aggressive deadlines

• Ability to work with technical and non-technical team members