Design, develop, and implement advanced data science models and machine learning solutions for key business use cases across online experience, marketing, merchandising, and store operations. Apply advanced data science techniques to large datasets and collaborate with cross functional groups to derive actionable insights and develop scalable AI solutions. Execute best-in-class advanced analytics with scalable and reusable codebase and models that solve business problems. Generate and test hypotheses that align with priority use case. Comply with analytics standards, including guidelines for tailoring analytics methodologies to specific use case needs (e.g., ML, AI, descriptive analytics). Define internal or external, batch or real-time streaming data needs, evaluate data quality, and extract/manipulate data in a "Big Data" environment. Create compelling interactive visualizations and presentations to enhance decision making capabilities throughout the company. Work with Data Engineering team as required to implement data pipelines and tools to ensure efficient and seamless execution of analytics. Be agile in identifying data issues and taking action to remediate. Provide support for business users to leverage insights and provide high value impact. Maintain an up-to-date view on methods being used in the data science community. May telecommute.
Requires a Master’s degree in Statistics, Computer Science, Business Analytics or related field and 2 years of experience as Data scientist or related occupation.Position requires:
1. Building data models and pipelines to process different types of large datasets.
2. Fluency with complex algorithms and analytics methodologies across multiple platforms and languages, including Google Cloud Platform.
3. SQL and Python.
4. Core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis, and machine learning techniques.
5. Visualization tools such as Tableau and Power BI.
6. Collaborating with business functions to deliver solutions that support decision making.
7. Analyzing data to identify deliverables, gaps, and inconsistencies.
8. Data management and data modeling.
9. Version control with Git using tools, including PyCharm and VS Code
Macy's is America’s store for life. The largest retail brand of Macy's, Inc. (NYSE:M) delivers quality fashion at affordable prices to customers at approximately 640 locations in 43 states, the District of Columbia, Puerto Rico, and Guam, as well as to customers in more than 100 international destinations through leading e-commerce site macys.com. Macy's inspires fashion exploration and discovery through the most desired family of exclusive brands for her, for him, for the home, and via our dynamic mobile and social platforms. We know the power of celebration, demonstrated through decades of memorable experiences created during Macy's 4th of July Fireworks® and Macy's Thanksgiving Day Parade®, as well as spectacular fashion shows, culinary events, flower shows, and celebrity appearances. Macy's flagship stores – including New York City’s Herald Square – are internationally renowned and preeminent destinations for tourists. With the collective support of our customers and employees, Macy's builds community and helps make a difference in every market we serve, supporting local and national charities by giving nearly $50 million each year, plus 146,000 hours of volunteer service. For more than 160 years, Macy’s has, and continues to, make life shine brighter for our customers, colleagues, and communities.
