H-E-B - San Antonio, TX

posted 3 days ago

San Antonio, TX
Food and Beverage Retailers

About the position

H-E-B's Corporate Planning and Analysis Team develops and maintains budgets and financial systems while providing current, reliable financial data, analysis, and technical information. As a Data Scientist II, your archetype is an ML / AI Business Solution Designer. Your passions include creating end-to-end business solutions packages by integrating multi-modals and data pipelines, innovating new ML algorithms to establish strong competitive advantage for H-E-B business, and designing and implementing different ML integration patterns to facilitate multi-modal orchestration. Once you're eligible, you'll become an Owner in the company, so we're looking for commitment, hard work, and focus on quality and Customer service. 'Partner-owned' means our most important resources--People--drive the innovation, growth, and success that make H-E-B The Greatest Omnichannel Retailing Company.

Responsibilities

  • Demand Transfer Models (NLP for Product Affinity, Cannibalization Model and Attraction Models (Halo), Multinomial Logit Models, Consumer Decision Trees, etc.)
  • Network Model and Graph Theory for demand transfer
  • Assortment Optimization (Assortment Cross-Elasticities, Assortment Linear Programming Optimization, Nested Logit Models, etc.)
  • Price Optimization (Price-Response Function, Price Elasticities with Competition, Price Differentiation, Capacity Allocation with Dependent Demands, Network Pricing Optimization, Markdown Optimization, Price Dynamic Optimization, etc.)
  • Serves H-E-B as a thought leader in selected mainstream ML / AI fields
  • Builds a concrete roadmap for ML solution maturity revolution
  • Creates end-to-end business solutions packages by integrating multi-modals and data pipelines
  • Designs / implements different ML integration patterns to facilitate multi-modal orchestration
  • Innovates new ML algorithms to establish strong competitive advantage for H-E-B business; ensures new algorithms are backed by solid math and science proof
  • Applies an inquisitive nature about open source algorithms, their theories, and their implementation
  • Grows expertise in constructing distributed machine learning pipeline from scratch

Requirements

  • A related degree or comparable formal training, certification, or work experience
  • 5+ years of experience in a retail or retail-related decision science role
  • Expertise / in-depth knowledge of business domain
  • Well-rounded experience integrating math / science and platform engineering
  • Programming language skills (SQL, R, Python, Scala, Java, C/C++)
  • ML optimization skills (GPU code optimization, Horovod, SparkMLlib optimization, Cython, JNI, Numba)
  • Mainstream ML / AI skills (deep learning, computer vision, NLP / NLU, reinforcement learning, meta-learning, federated learning)
  • Ability to grow expertise in constructing distributed machine learning pipeline from scratch
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