Data Science Senior Manager

Data Science Sr. Manager

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

Position Purpose: The Data Science Sr. Manager is responsible for leading a team of data scientists (individual contributors, technical experts, and/or people managers), ensuring that their efforts drive business profitability, increased efficiencies, and improved customer experience. This role harmonizes between the continuous drive towards data science research and learning and the needs of the business. As a Data Science Sr. Manager, you will provide executive summaries to all levels of the organization and leverage your business knowledge and network to identify opportunities to leverage data science solutions. This role is expected to lead the collaboration between Data Science Managers across the organization to align strategies and effectively manage talent. These responsibilities require effective communication skills, building relationships and partnerships, and leveraging business proficiency to solutions and recommendations.

Key Responsibilities:

• 50% People Management & Team Leadership - Provide leadership, mentorship, and coaching to direct reports and evaluate performance, execution, and contribution; Support Data Science Director in establishing a clear vision for the team and influencing reach with business partners; 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; Develop onboarding and training plan for both technical and soft skills that will ensure high level of capabilities within the team; Foster collaboration and alignment between different data science roles to develop a supportive and engaged team; Ensure best practices and world-class techniques are leveraged in the solutioning for business problems and future team reach; Drive team's results and celebrate accomplishments
• 15% Program 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; Be a champion and advocate for the team's capabilities, expertise, and needs
• 25% 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 lead the efforts of developing high-level strategy and optimizing talent management
• 10% 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