Manager of Data Science - pXI

HEB•San Antonio, TX

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 People Manager of Data Science, your archetype is a Data Scientist Mentor. Your passion is establishing connections between external community thought leaders H-E-B's internal community, bringing visibility of the latest ML / AI development so the H-E-B community can learn to adapt, and building our playbook, best practices, and guidelines to help elevate maturity in the H-E-B community. You'll lead a team of Data Scientists and direct analytic efforts across across supply chain, store operations, merchandising and marketing areas. You’ll partner with product managers to translate business strategy into scalable AI solutions, balance technical delivery with pragmatic business outcomes, and champion AI across the organization. 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. Do you have a: HEART FOR PEOPLE... willingness to mentor? HEAD FOR BUSINESS... ability to build connections between H-E-B and external thought leaders? PASSION FOR RESULTS... drive to explore options to optimize reuse / efficacy of shared assets?

Requirements

someone who can inspire and mentor data scientists on adoption of the latest ML / AI best practices and reusable assets
10 years of experience in a retail-related data / decision science role; experience managing data science teams across multiple projects
worked closely with product and program management on business and technical roadmap delivery
A related degree or comparable formal training, certification, or work experience
10+ years of experience in a retail or retail-related decision science role
5+ years of experience in management or technical leadership
Expertise in ML visualization flow
Expertise in optimizing distributed machine learning in a heterogeneous domain environment
Experience managing data science teams across multiple projects
Technical knowledge in programming languages: SQL, R, Python, Scala, Java, C/C++
Technical knowledge in big data / ML optimization: GPU code optimization, Horovod, Spark MLlib optimization, Cython, JNI, Numba
Technical knowledge in mainstream ML / AI: manifold learning, distributed clustering, graph network, hierarchical model, Bayesian network, deep learning, computer vision, NLP/NLU, reinforcement learning, meta-Learning, federated learning
Advanced presentation, solution-selling, and influencing skills
Strong project management, time management, and organization skills
Ability to train, mentor, and inspire others
Work in a fast-paced retail environment with frequently shifting priorities
Travel by car or plane with overnight stays
Work extended hours; sit for long periods

Responsibilities

Manages the Data Science team
Establishes connections between external community thought leaders and the H-E-B internal community; collaborates cross-functionally to identify opportunities / develop initiatives that support H-E-B's growth in technical leadership and excellence
Brings visibility of latest ML / AI development so the H-E-B community learns how to adapt; builds playbook, best practices, and guidelines to help elevate the maturity in H-E-B community
Seeks the latest modern ML / AI development in the industry
Constantly explores the needs of best practices and guidelines to optimize reuse and efficacy of shared assets
Acquires prevalent knowledge of ML / AI used by competitors or in similar industries
Constantly evaluates design and adoption path of the latest ML / AI developments
Inspires DS teams to co-author papers and blogs to promote H-E-B data science branding in the community
Mentors data science teams; motivates them to adapt the mindset of constant change and innovation; actively develops next generation of data science leaders through mentoring, development, and training

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