Senior Director, Enterprise Data Science at Macys in New York, NY

About:

Macy’s is proudly America’s Department Store. For more than 160 years, Macy’s has served generations at every stage of their lives. Customers come to us for fashion, value and celebration. Now is an exciting time to join Macy’s, Inc. The face of retail is changing, and change requires innovation.

Macy’s Digital business is in the top 10 largest in the U.S. (#1 largest in NYC) and has driven 10 consecutive years of double-digit growth. We’re building a new type of customer-centric shopping experience - at the intersection of content, commerce, and technology - to help customers find and buy products they love.

Do you want to collaborate with a smart and talented team in a fun work environment? This is a unique opportunity to join an established company that is investing in development and growing digital business at scale. Gain first-hand experience defining the future of online and physical commerce. With a constant influx of exciting and challenging problems to solve - you'll never have a boring day at the office. We also offer many roles with the freedom to build and lead a team. Join Macy’s Digital to grow your career and help shape the future of an iconic brand.

Job Overview:

The Senior Director, Enterprise Data Science is responsible for leading enterprise data science and analytics to effectively execute on priority use cases for Macy’s, Inc. The Sr. Director will drive analytics and algorithm integration and development for use cases and establish norms, standards and a data-driven culture throughout the organization. The Sr. Director will lead and build a team of Data Scientists who will set the standard for analytics across the organization and partner closely with business units to support analytics execution.

Essential Functions:

Analytics:

• Deploy best-in-class advanced analytics and ensure scalability and reusability of codebase and models while establishing standardized enterprise methodologies.
• Define and enforce analytics standards, including guidelines for tailoring analytics methodologies to specific use case needs (e.g., ML, AI, descriptive analytics).
• Drive use case execution, coordinating closely with Business Units to work on priority use cases identified as areas for Enterprise Data & Analytics (EDA) support. Set analytical methodologies for critical insights.
• Institute quality control and ethical guidelines for algorithms, code, and outputs.
• Work with Data and Solution Architecture teams to identify and implement data pipelines and tools to ensure efficient and seamless execution of analytics.

Culture:

• Create and foster community of practice for data science and analytics.
• Increase agility in identifying data issues and taking action to remediate.
• Drive change management to create an understanding of potential applications of advanced analytics and data science.
• Encourage user adoption of analytical tools and methods, and embrace data in strategic business decisions.
• Create awareness, knowledge and conviction around data-driven practices and behaviors, increasing digital IQ of organization.

Leadership:

• Leader with a passion for data and analytics who can build credibility for the Enterprise Data & Analytics team within the organization.
• Lead the alignment of best in class analytics for the total enterprise including coordination with senior leadership.
• Partner closely with Technology and Business Units to drive adoption, as well as provide direct analytical support where needed.
• Balance both leading a team and engage directly with the work needed to accomplish the priority use cases.
• Coach direct reports as they build strategies and roadmaps.
• Create and foster career development and growth paths for team members in alignment with company and personal objectives.
• Assist direct reports with ongoing prioritization and resource allocation to ensure that the crucial business initiatives are delivered.
• Provide guidance on recruitment and career pathing for analytics resources
• Balance team resourcing and talent management
• Demonstrate Macy’s leadership commitments of promoting diversity and inclusion, encouraging growth, creating connection and driving performance.

Key Performance Indicators:

• Integration, development, and deployment of algorithms and methodologies for analytics use cases.
• Adoption of coding and methodology best practices across the enterprise.
• Additional metrics dependent upon prioritized use cases supported (e.g., lift, customer acquisition, retention, etc).
• Annualized value to business vs. expense

Qualifications and Competencies:

• Bachelor's Degree from a 4-year college or university
• Master's Degree in related field preferred
• 5+ years direct experience
• BA or BS Degree required; Masters or PhD in math, statistics, computer science, or related discipline preferred.
• Data scientist with over 10+ years of experience in the field.
• 5+ years of leading & managing a team of data scientists.
• Fluent in complex algorithms and analytics methodologies across multiple platforms and languages.
• Analytics expert with experience in delivering
• Customer-centric and experienced with cross-functional collaboration.
• Analytics expert with experience in delivering robust analytics use cases across business units with experience in cross-functional collaboration.
• Community builder who can foster a data and analytics culture and support data-driven thinking and discussions.
• Ability to effectively share technical information, communicate technical issues and solutions to all levels of business
• Able to juggle multiple projects - can identify primary and secondary objectives, prioritize time and communicate timeline to team members
• Ability and desire to take product/project ownership
• Ability to think creatively, strategically and technically
• Ability to work a flexible schedule based on department and Company needs.