Data Science Manager

The Home Depot • Atlanta, GA

1d

About The Position

The Solutions Engineering Manager sits between data engineering and application engineering, leading a team of individual-contributor data and application engineers who build and evolve data pipelines and self-service analytics, and turn prototype applications into dependable solutions. The role balances lasting, trustworthy data and applications with the business’s need for speed, partnering with platform teams to move solutions into a supported environment. The manager provides executive summaries to business leadership and translates strategy into execution, using strong communication and relationship-building skills and sufficient analytics, engineering, and business proficiency to deliver reliable solutions.

The position leads and develops team members, manages resources and programs, aligns projects with business objectives, and identifies opportunities to apply data science. It also advances data science and analytics practices by exploring technical developments and promoting repeatable, production-ready solutions.

Requirements

• Must be at least 18 years of age.
• Must be legally permitted to work in the United States.
• A bachelor’s degree or equivalent in a job-related field, or the knowledge, skills, and abilities typically acquired through completing such a program.
• At least 8 years of work experience.

Nice To Haves

• 9 or more years of experience spanning data engineering, analytics engineering, or application engineering.
• Previous people-management or project-team management experience.
• Experience refactoring or hardening prototype data products or applications into secure, reliable, production-quality solutions.
• Experience designing and maintaining tested, version-controlled data models or transformations, such as Dataform or dbt, preferably with Google BigQuery or SQL.
• Experience applying modern engineering practices, including version control, automated testing, and deployment pipelines, to data or application code.
• Experience partnering with platform, infrastructure, or security teams to move data products or applications into a supported, sanctioned environment.
• Familiarity with generative AI-enabled analytics or self-service business intelligence tools.

Responsibilities

• Lead, mentor, coach, and evaluate the performance, execution, and contributions of individual-contributor Data Scientists.
• Attract, retain, and develop talent; support employees’ business knowledge and technical skills through development plans and regular progress assessment.
• Document processes and job-specific requirements, and develop technical and soft-skills onboarding and training plans.
• Manage resources to align with strategic initiatives and business needs, foster a supportive and engaged team, and recognize team accomplishments.
• Support the team in designing and developing algorithms and models for large datasets to generate business insights.
• Prioritize and assign projects based on factors such as funding, return on investment, and the nature of the work.
• Manage team programs to support consistent execution, balanced resources, and quality solutions.
• Collaborate with program managers and business partners to align objectives and expectations and ensure project delivery.
• Serve as an escalation point for project issues and provide executive updates on program effectiveness, team accomplishments, findings, recommendations, and internal and external impacts.
• Identify business opportunities for data science and advocate for the team’s capabilities.
• Build trust and collaboration with internal customers and cross-functional teams, and align with IT support models, collaboration practices, tools, and governance.
• Collaborate with other data science managers on organizational strategy and talent management.
• Stay informed about developments in data science, technical skills, and data sources.
• Develop repeatable data science and analytics solutions, such as codified data products, project documentation, and process flowcharts.
• Promote best practices and a vision for data analysis and model productionalization.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager