What are the responsibilities and job description for the Lead Data Scientist, Search position at Home Depot Management Company, LLC?
Position Purpose :
The Lead Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role assists in the development of the Home Depot advanced analytics infrastructure that informs decision making by applying expertise of both business and Advanced Analytics Modeling techniques. Lead Data Scientists focus on seeking out business opportunities to leverage data science as a competitive advantage. Based on the specific data science team, this role has expertise in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP.
As a Lead Data Scientist, you will be responsible for large data science projects, identifying opportunities to leverage best technology and approach, and mentoring data scientists on the project team. This role is expected to own the library of reusable algorithms for future use, ensuring developed codes are documented. This role supports the building of skilled and talented data science teams by providing input to staffing needs and participating in the recruiting and hiring process. In addition, this role leads data science communities across several business units.
Key Responsibilities :
- 30% Solution Development - Utilize expertise when designing and developing algorithms and models to use against large datasets to create business insights; Make appropriate selection, utilization and interpretation of advanced analytics methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers / partners; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation
- 25% Project Management & Team Support - Lead and manage large and complex projects and teams; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team; Serve as a technical subject matter expert (SME) for one or more data science methods, both predictive and prescriptive; Lead data science communities across several business units
- 20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide technical education on advanced analytics to data science community; Partner with IT to understand potential for new tools and ways to maintain technical agility for data science; Actively seek out new business opportunities to leverage data science as a competitive advantage
- 25% Technical Exploration & Development - Seek further knowledge on key developments within data science by attending conferences and publishing papers; 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; Define best practices and develop clear vision for data analysis and model productionalization; Ownership of library of reusable algorithms for future use, ensure developed code / models are documented; Develop mastery in one or more prescriptive modeling techniques, like optimization, computer vision, recommendation, search or NLP
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