Principle, Data Scientist

2 weeks ago

Cranberry Twp, PA, United States Giant Eagle Full time
Job Summary

This role will leverage advanced analytics, machine learning and data wrangling techniques to influence, shape and interact with our customers across marketing and merchandising. You will create predictive and prescriptive models that reaches millions of customers. You are a passionate individual with a knack for discovering solutions hidden in large data sets, working with a wide range of stakeholders, and building personalized experiences at scale.

Job Description

  • Experience Required: 5-10+ years combined full-time experience in data science, customer analytics or machine learning;
  • 7+ years of experience using advanced algorithms, programming languages (Python, R, SQL), or technologies in the development of technical analytics solutions or capabilities;
  • 7+ years of experience analyzing/modelling very large datasets and dimensionality reduction;
  • 7+ years of experience in SQL, data wrangling and feature engineering
  • Experience Desired: Large databases; Passionate about data, SL/ML; Understanding of AI algorithms; Strong business acumen to link analysis to business impact
  • Education Desired: Bachelors Degree in Mathematics, Statistics, Analytics, Data Science or related discipline
  • Experience Required: Demand planning, inventory forecasting, inventory planning
  • Nice to have retail experience industry.
Job Responsibilities
  • Develop data science project architectures to enable large-scale solutions
  • Support marketing initiatives with data-driven recommendations on audience, market, and item selection
  • Maintain and automate data science solutions and common code bases for repeatable tasks
  • Support new and current team members in being onboarded to GE data and Databricks
  • Assist in evaluation of potential DS consultants/partners
  • Implementation of item/location level demand planning to ensure efficient supply chain and holding power
  • Responsible with supporting the delivery of desired in stock levels while hitting financial targets

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