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Data Science Manager at Home Depot, STORE SUPPORT CENTER

Data Science Manager at Home Depot in STORE SUPPORT CENTER. Full-time. Est. up to $200k. Apply with swipeandhired.

With a career at The Home Depot, you can be yourself and also be part of something bigger.

Position Purpose:
The Solutions Engineering Manager sits between data engineering and application engineering, leading a team of data and application engineers (individual contributors) who build and evolve the data pipelines and self-service analytics the business relies on, and harden prototype applications into dependable solutions. This role balances the rigor of building lasting, trustworthy data and applications with the business's need for speed, partnering with platform teams to bring solutions into a supported environment. As a Solutions Engineering Manager, you will provide executive summaries to business leadership and translate strategy into execution for your team. These responsibilities require strong communication skills, relationship-building across technical and business stakeholders, and enough analytics, engineering, and business proficiency to deliver solutions the organization can rely on.

Key Responsibilities:

40% People Management & Team Leadership - Provide leadership, mentorship and coaching to Data Scientists (individual contributors) and evaluate performance, execution, and contribution; Attract, retain and develop top talent to build an effective and high performing team; Support team in development of business knowledge and technical skills with clear plans and regular assessment of progress; Ensure appropriate processes and job-specific requirements are properly documented; Develop onboarding and training plan for both technical and soft skills that will ensure high level of capabilities within the team; Manage resources effectively to align with strategic initiatives and business needs; Foster collaboration with team members to develop a supportive and engaged team; Support team in the design and development of algorithms and models to use against large datasets to create business insights; Drive team's results and celebrate accomplishments
25% Project Management - Prioritize and assign projects by striking a balance between a variety of factors, like funding, return on investment, innovative or challenging work, among others; Manage programs for the team to ensure consistency of execution, balance of resources and quality solutions; Collaborate with program managers and business partners to align on objectives and expectations and ensure project teams deliver against them; Serve as escalation point for any issues or difficulties with specific projects; Provide executive updates to leaders at all levels of the organization on program effectiveness, team accomplishments, summary of findings and recommended solution, and explain internal and external impacts
15% Strategy & Business Development - Leverage extensive business knowledge and relationships to seek out new business opportunities to leverage data science and advocate for team's skills; Effectively develop trust and collaboration with internal customers and cross-functional teams; Ensure alignment with IT support model, collaboration, tools and governance to enable data scientists to be most effective in executing their roles; Collaborate with other data science managers across the organization to establish high level strategy and optimize talent management
20% Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Ensure best practices and vision for data analysis and model productionalization are leveraged

Direct Manager/Direct Reports:

This position typically reports to Senior Manager or above
This position has Direct Reports & manages programs

Travel Requirements:

Typically requires overnight travel 5% to 20% of the time.

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:

9+ years of experience spanning data engineering, analytics engineering, or application engineering
Previous people or project team management experience.
Demonstrated experience refactoring or hardening prototype data products or applications into secure, reliable, production-quality solutions.
Demonstrated experience designing and maintaining tested, version-controlled data models or transformations (e.g., Dataform, dbt), preferably against Google BigQuery or SQL.
Experience with modern engineering practices — version control, automated testing, and deployment pipelines — applied 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

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:

Preferred Years of Work Experience:

No additional years of experience

Minimum Leadership Experience:

None

Preferred Leadership Experience:

None

Certifications:

None

Competencies:

Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs
Builds Effective Teams: Building strong-identity teams that apply their diverse skills and perspectives to achieve common goals
Builds Networks: Effectively building formal and informal relationship networks inside and outside the organization
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences
Develops Talent: Developing people to meet both their career goals and the organization's goals
Directs Work: Provides direction, delegating and removing obstacles to get work done
Drives Engagement: Creating an environment where people are motivated to do their best to help the organization achieve its objectives
Drives Vision and Purpose: Painting a compelling picture of the vision and strategy that motivates others to action
Instills Trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity
Interpersonal Savvy: Relating openly and comfortably with diverse groups of people
Organizational Savvy: Maneuvering comfortably through complex policy, process, and people-related organizational dynamics
Persuades: Using compelling arguments to gain the support and commitment of others
Strategic Mindset: Seeing ahead to future possibilities and translating them into breakthrough strategies