Lead Data Scientist - Generative AI

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.

Responsibilities:
Design and implement LLM fine-tuning techniques for specific tasks and applications. Develop and maintain production-grade LLM inference pipelines. Develop domain specific knowledge base for LLM (Vector Store, Knowledge Graph, structured data, multi-modal data) Monitor and analyze LLM performance, identify and address potential biases and fairness issues. Stay up-to-date on the latest advancements in LLM research and development. Contribute to the development of internal tooling and infrastructure for LLM development and deployment. Document and communicate LLM technical concepts to a broader audience.
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
  Direct Manager/Direct Reports:
  This position typically reports to manager or above This position has 0 Direct Reports and leads/manages projects
  Travel Requirements:
  Typically requires overnight travel less than 10% 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. Demonstrated expertise in predictive modeling, data mining and data analysis Demonstrated expertise utilizing statistical techniques to identify key insights that help solve business problems
  Preferred Qualifications:
  Master's degree in Computer Science, Artificial Intelligence, or a related field (or equivalent experience). PhD highly preferred. Proven experience in machine learning, with a strong focus on Natural Language Processing (NLP). In-depth knowledge of deep learning architectures, particularly transformers. Experience with LLM frameworks such as TensorFlow or PyTorch. Experience with cloud platforms like Google Cloud AI Platform, Amazon SageMaker, or Microsoft Azure Machine Learning. Excellent programming skills in Python (and ideally other languages like Java or C++). Strong problem-solving and analytical skills. Excellent communication and collaboration skills.
  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:
  10
  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 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 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 Cultivates Innovation: Creating new and better ways for the organization to be successful Develops Talent: Developing people to meet both their career goals and the organization's goals Instills Trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement Persuades: Using compelling arguments to gain the support and commitment of others Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels Strategic Mindset: Seeing ahead to future possibilities and translating them into breakthrough strategies Tech Savvy: Anticipating and adopting innovations in business building digital and technology applications