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Associate Data Scientist, Online
  • Python
  • Machine Learning
  • Excel
  • Scala
  • Deep Learning
The Home Depot
Atlanta, GA
142 days ago

POSITION PURPOSE

The Associate Data Scientist will help lead efforts to ensure Data Quality & Data Governance across The Home Depot’s multi-million item catalog that will directly impact how customers & business stakeholders consume information about the products we sell. By leveraging machine learning techniques & statistical methods, we aim to maintain the highest standard of data possible while developing extremely scalable and production ready models. You will work directly with cross-functional partners including engineering, analytics, UX, & product management. This candidate will frequently present key findings to leadership, and ultimately help drive strategic business decisions that maximize value for our customers.

MAJOR TASKS, RESPONSIBILITES AND KEY ACCOUNTABILITIES

50% - Model Preparation: Establish scalable, efficient processes for large scale data analyses, model development and model implementation

30% - Model Development and Deployment: Design and develop algorithms and models to use against large datasets to create business insights

20% - Communication and Visualization: Present analysis and resulting recommendations to senior management; Leverage data to present a compelling business case to optimize investments and operations

NATURE AND SCOPE

This position reports to the Senior Manager Data Science.

This position has 0 direct reports.

ENVIRONMENTAL JOB REQUIREMENTS

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. Additional Environmental Job Requirements:
Essential Skills:

MINIMUM QUALIFICATIONS
Must be eighteen years of age or older.
Must be legally permitted to work in the United States.
Additional Minimum Qualifications:

Education Required:

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

Years of Relevant Work Experience: 2 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.

Preferred Qualifications:

  • Master's / PhD degree preferred in Computer Science, Statistics, or similar STEM fields
  • Proficiency in Python
  • Experience with developing and deploying production level models in Cloud environments (GCP/AWS)
  • Comfortable with both classical machine learning methods as well as deep learning
  • Strong foundation of statistical methods / probability theory
  • Previous industry experience with (2) or more of the following;
    • Anomaly Detection
    • Similarity Detection
    • Entity Recognition & Entity Resolution
    • Multivariate Forecasting
    • Data Standardization
    • Data Imputation
    • Extreme label classification

Ability to convey complex or technical ideas and processes in easy-to-understand terms to diverse audiences

Excellent written and verbal communication skills

Ability to build scalable systems that analyze huge data sets and make actionable recommendations Strong communication and data presentation skills 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

Knowledge, Skills, Abilities and Competencies: Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm

Collaborates - Building partnerships and working collaboratively with others to meet shared objectives

Communicates Effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences

Customer Focus - Building strong customer relationships and delivering customer-centric solutions Drives Results - Consistently achieving results, even under tough circumstances
Manages Conflict - Handling conflict situations effectively with minimal noise

Nimble Learning - Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder

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