Company Overview
Macy’s is America’s store for life. As the largest retail brand under Macy’s, Inc. (NYSE: M), Macy’s offers quality fashion at affordable prices to customers across approximately 640 locations spanning 43 states, the District of Columbia, Puerto Rico, and Guam. Additionally, Macy’s serves customers in over 100 international destinations through its premier e-commerce platform, macys.com.
Macy’s encourages fashion discovery and exploration through an extensive portfolio of exclusive brands tailored for women, men, and the home, complemented by engaging mobile and social media experiences. The brand is synonymous with celebration, creating unforgettable moments through iconic events such as the Macy’s 4th of July Fireworks® and the Macy’s Thanksgiving Day Parade®, alongside spectacular fashion shows, culinary showcases, floral exhibitions, and celebrity appearances.
Macy’s flagship stores, including the renowned Herald Square location in New York City, are internationally recognized as must-visit destinations for tourists. With the ongoing support of its customers and employees, Macy’s actively contributes to communities nationwide by supporting local and national charities with nearly $50 million in donations annually, along with 146,000 hours of volunteer service.
For over 160 years, Macy’s has been dedicated to brightening the lives of its customers, colleagues, and communities, continuing to inspire and make a meaningful impact everywhere it serves.
Role Overview
As a Senior Data Analyst, you will play a critical role in driving strategic decisions and improving operational efficiency. Collaborating closely with cross-functional teams—including strategy, business operations, and physical operations—you will deliver actionable insights, craft compelling data stories, and develop impactful data visualizations. Your expertise in SQL, Python/R, and advanced analytics tools will uncover key trends that support both long-term planning and day-to-day business improvements.
Key Responsibilities
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Data Analysis & Reporting:
Extract, manipulate, and analyze large datasets using SQL and advanced analytical methods. Develop automated reports and dashboards that deliver valuable business insights. -
Advanced Analytics & Modeling:
Create and validate predictive models with Python or R to forecast trends and operational challenges. Build sophisticated data models reflecting the complexities of business operations and performance. -
Data Visualization:
Design and maintain polished, interactive dashboards and visualizations that clearly communicate findings to technical and non-technical audiences alike. -
Stakeholder Management:
Partner with cross-functional teams to understand business needs and translate them into meaningful analytics projects. Present findings and strategic recommendations to executive leadership and key stakeholders. -
Strategic & Operational Support:
Work alongside strategy and business operations teams to craft data-driven approaches that enhance performance and fuel growth. Track key performance indicators (KPIs) and identify opportunities for improvement. -
Process Improvement & Innovation:
Continuously seek to enhance data methodologies and processes. Serve as a thought leader, contributing to the company’s overall data strategy.
Education & Experience
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Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, Data Science, or a related discipline.
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Minimum of 4 years’ experience in analytics, business intelligence, or data science.
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Experience in the technology sector or startup environment is a plus.
Technical Skills
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Expert proficiency in SQL.
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Hands-on experience with data warehousing (Snowflake), data transformation (dbt), and data visualization tools such as Sigma Computing, Tableau, or Looker.
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Strong coding skills in Python or R.
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Advanced analytics and modeling expertise.
Soft Skills
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Excellent analytical, problem-solving, and strategic thinking abilities.
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Strong communication and interpersonal skills with a proven track record of cross-departmental collaboration.
Preferred Qualifications
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Experience in fast-paced tech startups or dynamic technology companies.
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Familiarity with cloud data platforms like AWS, Google Cloud, or Azure.
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Knowledge of growth analytics, marketing analytics, and MarTech tools.