Bloomingdale's

Role Description 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. Qualifications - Master’s degree in Statistics, Computer Science, Business Analytics or related field. - 2 years of experience as Data Scientist or related occupation. Requirements - Building data models and pipelines to process different types of large datasets. - Fluency with complex algorithms and analytics methodologies across multiple platforms and languages, including Google Cloud Platform. - SQL and Python. - Core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis, and machine learning techniques. - Visualization tools such as Tableau and Power BI. - Collaborating with business functions to deliver solutions that support decision making. - Analyzing data to identify deliverables, gaps, and inconsistencies. - Data management and data modeling. - Version control with Git using tools, including PyCharm and VS Code.