Associate Data Scientist - Decision Analytics (Customer Experience Economics)

Home Depot; Roswell (GA); On-site; USD 90,000 - 125,000; Full time

Job summary

Home Depot seeks an Associate Data Scientist on the Customer Experience Economics team to advance profitability, efficiency, and customer satisfaction through data-driven insights. You will collaborate with Data Scientists and business partners across Customer, Delivery, and Finance to translate analytics into strategic recommendations.

The role emphasizes learning, agility, and storytelling with data, balancing technical rigor with clear communication to leadership and non-technical audiences.

Qualifications

• Bachelor's degree in a related field or equivalent
• 3+ years of experience in business intelligence and analytics
• Experience with Python, SQL and data visualization tools
• Experience with data mining and predictive modeling

Responsibilities

• 70% Solution Development: design and develop models and algorithms on large datasets to generate insights
• 20% Communicating Results: present insights and recommendations to both technical and non-technical audiences
• 10% Technical Learning: stay current with trends and continuously enhance analytics skills

Skills

Python

Data visualization

Statistics

Data mining

BI analytics

Education

Master's degree in quantitative field

Tools

Google BigQuery

SQL

Tableau

Excel

PowerPoint

Job description

Position Purpose:

The Associate Data Scientist on the Customer Experience Economics team is responsible for supporting data science initiatives that drive business profitability, operational efficiencies, and an improved customer experience. Operating within Decision Analytics-an internal data science team embedded within Finance-this role enjoys a unique organizational vista point, allowing the incumbent to partner across multiple business domains including Customer, Delivery, and broader Finance initiatives. This dynamic environment requires a highly curious, agile learner who can rapidly adapt to new business contexts and data landscapes. You'll work with other data scientists and business partners to solve real business problems and turn the results into insights that enable strategic decision-making for leadership. You'll also learn to tell the story behind the data and take ownership of your work, shaping it so it makes sense for a range of technical and leadership levels.

Key Responsibilities:

• 70% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Supports data science projects by conducting effective analysis to solve business problems; Executes tasks with high levels of efficiency and quality; Consults with Data Scientist or Sr. Data Scientist on appropriate selection, utilization and interpretation of advanced analytical methodologies; Learn about the assigned business areas to provide better solutions by incorporating business-specific knowledge
• 20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical audience; Support preparation of reports, updates and/or presentations related to progress made on a project or solution; Highlights potential impacts of recommendations to drive alignment and appropriate implementation
• 10% Technical Learning - Keep up to date on industry trends, best practices and emerging methodologies; Continually develop skills and expertise in data analytics concepts and methodologies; Identify opportunities to apply learnings

Direct Manager/Direct Reports:

This position reports to manager or above

This position has 0 direct reports

Travel Requirements:

No travel required.

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.

Working Conditions:

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

Minimum Qualifications:

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

Preferred Qualifications:

• Master's degree in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience
• 3+ years of experience in business intelligence and analytics
• Working knowledge of Microsoft Excel and Power Point
• Experience in a modern scripting language (preferably Python)
• Experience running queries against data (preferably with Google BigQuery or SQL)
• Experience in predictive modeling, data mining and data analysis
• Experience with data visualization software (preferably Tableau)
• Experience utilizing statistical techniques to identify key insights that help solve business problems
• Basic knowledge or exposure to Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP
• Basic knowledge or exposure to predictive modeling, data mining and data analysis

Minimum Education:

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.

Preferred Education:

No additional education

Minimum Years of Work Experience:

0

Preferred Years of Work Experience:

No additional years of experience

Minimum Leadership Experience:

None

Preferred Leadership Experience:

None

Certifications:

None

Competencies:

• Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm
• Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals
• 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
• Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder
• Optimizes Work Processes: Knowing the most efficient and effective processes to get thing