Macy's
Job Description
Execute best-in-class advanced analytics with scalable and reusable codebase and models that solve business problems. Coordinate closely with Sr & Lead Data Scientists to generate and test hypotheses that align with priority use cases. Comply with analytics standards, including guidelines for tailoring analytics methodologies to specific use case needs (e.g., ML, AI, descriptive analytics). Define batch or real-time streaming data needs, evaluate data quality, and extract/manipulate data in a "Big Data" environment. Define internal and external data needs, quality measures and suitability for use. Support the building of predictive models to identify opportunities to provide further support to Business Units. Generate high impact visualizations to communication findings generated from data. Work with Data and Solution Architecture teams as required to implement data pipelines and tools to ensure efficient and seamless execution of analytics. Support Sr & Lead Data Scientists to build enterprise-wide data assets that will accelerate delivery of new use cases and help train machine learning models. Employer will accept a Master's degree in Computer Science, Computer Engineering, Business Analytics, or related field. Position Requirements
Complex algorithms and analytics methodologies across multiple platforms and languages; Communication with non-technical functions to deliver solutions that support decision making; Core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis and machine learning techniques; Utilizing programming languages to perform analytical modeling, including Python and SQL; Building and deploying analytical models; Code versioning and managing code base in Git and Gitlab products.
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Execute best-in-class advanced analytics with scalable and reusable codebase and models that solve business problems. Coordinate closely with Sr & Lead Data Scientists to generate and test hypotheses that align with priority use cases. Comply with analytics standards, including guidelines for tailoring analytics methodologies to specific use case needs (e.g., ML, AI, descriptive analytics). Define batch or real-time streaming data needs, evaluate data quality, and extract/manipulate data in a "Big Data" environment. Define internal and external data needs, quality measures and suitability for use. Support the building of predictive models to identify opportunities to provide further support to Business Units. Generate high impact visualizations to communication findings generated from data. Work with Data and Solution Architecture teams as required to implement data pipelines and tools to ensure efficient and seamless execution of analytics. Support Sr & Lead Data Scientists to build enterprise-wide data assets that will accelerate delivery of new use cases and help train machine learning models. Employer will accept a Master's degree in Computer Science, Computer Engineering, Business Analytics, or related field. Position Requirements
Complex algorithms and analytics methodologies across multiple platforms and languages; Communication with non-technical functions to deliver solutions that support decision making; Core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis and machine learning techniques; Utilizing programming languages to perform analytical modeling, including Python and SQL; Building and deploying analytical models; Code versioning and managing code base in Git and Gitlab products.
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