Macy's-posted 10 months ago
Full-time • Executive
Bridgewater Township, NJ
General Merchandise Retailers

Be part of an amazing story. Macy's is more than just a store. We're a story. One that's captured the hearts and minds of America for more than 160 years. A story about innovations and traditions…about inspiring stores and irresistible products…about the excitement of the Macy's 4th of July Fireworks, and the wonder of the Thanksgiving Day Parade. We've been part of memorable moments and milestones for countless customers and colleagues. Those stories are part of what makes this such a special place to work. Job Overview The VP, Enterprise Data Science is responsible for setting and owning the enterprise strategy of data science and machine learning, building best-in-class data science teams, modernizing data science and machine learning technology and platform, leading data science chapter across Macy's Inc. to effectively execute on priority use cases. The VP will drive analytics and algorithm integration and development for use cases and establish norms, standards and a data-driven culture throughout the organization. The VP will lead and build a team of Data Scientists and Machine Learning Engineers who will set the standard across the organization and partner closely with business units to support execution and productionizing solutions. The VP will report to the SVP of Enterprise Data & Analytics, who leads Enterprise Data & Analytics to accelerate digital transformation and value delivery from data and analytics, and coordinate efforts across the enterprise.

  • Set enterprise roadmap and deploy best-in-class advanced analytics and ensure scalability and reusability of codebase and models while establishing standardized enterprise methodologies.
  • Define and enforce data science and machine learning standards, including guidelines for tailoring analytics methodologies to specific use case needs.
  • Lead data science chapter across all business and technology teams and align data science strategies to business priorities.
  • Advance machine learning capabilities at Macy's Inc to empower business decisions with speed and scale.
  • Partner with business stakeholders to optimize the design of end-to-end data science & machine learning solutions.
  • Institute quality control and ethical guidelines for algorithms, code, and outputs.
  • Drive innovation, technical excellency, and work with product management and engineering to identify and implement data tools.
  • Create and foster community of practice for data science and machine learning.
  • Drive innovation and change management to create an understanding of potential applications of advanced analytics and data science.
  • Lead the enterprise agenda for data science and machine learning and drive alignment with senior leadership team.
  • Create and foster career development and growth paths for team members in alignment with company and personal objectives.
  • Promote Macy's data science and machine learning teams and work with external data science community.
  • Bachelor's degree or equivalent work experience required.
  • Data scientist with over 15 years of experience in the field.
  • 10 years of leading & managing a large team of data scientists focused on enterprise solutions.
  • Experience in retail or consumer industry is strongly preferred.
  • Demonstrated track record of developing, articulating, and driving a strategy of where and how data science and machine learning can create value.
  • Fluent in complex algorithms and analytics methodologies across multiple platforms and languages.
  • Ability to effectively share technical information and communicate technical issues and solutions to all levels of business.
  • Strong executive presence with ability to communicate complex messages and trade-offs.
  • Ability to influence a diverse group of stakeholders.
  • Strong leadership skills - ability to lead people and teams.
  • Experience in delivering data science initiatives and transforming data into business value in the retail/consumer context.
  • Community builder who can foster a data and analytics culture.
  • Comprehensive health and wellness coverage.
  • 401(k) match to invest in your future.
  • Paid time off and eight paid holidays.
  • Continuous learning and leadership development.
  • Merchandise discounts.
  • Performance-based incentives.
  • Annual merit review.
  • Employee Assistance Program with mental health counseling and legal/financial advice.
  • Tuition reimbursement.
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