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    Principal Data Scientist - Grand Rapids, United States - Meijer

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    Description
    As a family company, we serve people and communities. When you work at Meijer, you're provided with career and community opportunities centered around leadership, personal growth and development. Consider joining our family – take care of your career and your community

    Meijer Rewards
    Weekly pay

    Scheduling flexibility

    Paid parental leave

    Paid education assistance

    Team member discount

    Development programs for advancement and career growth

    Please review the job profile below and apply today

    This is a hybrid role meaning you have to be in our Grand Rapids office Monday - Wednesday. Relocation Assistance may potentially be provided.


    The Data Science team at Meijer leads the strategy, development and integration of Machine Learning and Artificial Intelligence at Meijer.

    Data Scientists on the team will drive customer loyalty, digital conversion, and system efficiencies by delivering innovative data driven solutions.

    Through these solutions, the data scientists drive material business value, mitigating business and operational risk, and significantly impacts the customer experience.

    This role works directly with product development, merchandising, marketing, operations, ITS, ecommerce, and vendor partners.

    The position will lead, consult or oversee multiple highly complex data science projects/programs/domains that have significant impacts and require in-depth technical knowledge across multiple specific architecture disciplines such as technology, solution, business, or information/data.

    .

    What You'll Be Doing:
    Deliver against the overall data science strategy to drive in-store and digital merchandising, marketing, customer loyalty, and operational performance
    Partner with product development to define requirements which meet system and customer experience needs for data science projects
    Partner with Merchandising, Supply Chain, Operations and customer insights to understand the journey that will be improved with the data science deliverables
    Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs
    Partner with product development and technology teams to deploy pipelines into production MLOps environment following Safe Agile methodology

    You will architect, design, and lead the development and implementation of machine learning algorithms and models for a data science capability within Digital Services, Merchandising, Marketing, Supply Chain and Operations.

    Designs, codes, and implements new industry leading design patterns in data science, to create the convention/technique/practice that teams are accountable to follow.

    Foster a culture of innovation by keeping up-to-date with the latest industry trends and research across data science, AI and retail.

    Mentors data science teams and promotes a culture of curiosity, accountability, & enthusiasm.
    Provides data science strategy to ensure code modernization and industry standard patterns for data science.
    Provides guidance to development teams within domain (Commerce, Services or Mobile).
    Leads non-functional requirements (NFRs) such as security, reliability, performance, maintainability, scalability, and usability related to data science.

    Promotes the implementation of new technology, solutions, and methods to improve business processes, efficiency, effectiveness, and value delivered to customers.

    Proactively identify data driven solutions for strategic cross-functional initiatives, develop and present business cases, and gain stakeholder alignment of solution
    Responsible to define, document & follow best practices & approve for ML/AI development at Meijer
    Own communication with data consumers (internal and external) to ensure they understand the data science products, have the proper training, and are following the best practices in application of data science products
    Define and analyze Key Performance Indicators to monitor the usage, adoption, health and value of the data products
    Identify and scope, in conjunction with IT, the architecture of systems and environment needs to ensure that data science systems can deliver against strategy
    Build and maintain relationships with key partners, suppliers and industry associations and continue to advance data science capabilities, knowledge and impact
    This job profile is not meant to be all inclusive of the responsibilities of this position; may perform other duties as assigned or required


    Education:
    Advanced Degree (MA/MS, PhD) in Data Science, Computer Science, Mathematics, Statistics, Economics, or related quantitative field

    Certifications:
    Azure Data Science Associate, Azure AI, Safe Agile

    What You Bring with You (Qualifications):8+ years of relevant data science experience in an applied role – preferable w/in retail, logistics, supply chain or CPG with a focus on NLP and AI
    Advanced and hands on experience using: Python, Databricks, Azure ML, Azure Cognitive Service, Ads Data Hub, BIQuery, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK
    Experience with Azure Cloud technologies including Azure DevOps, Azure Synapse, MLOps, GitHub
    Solid experience working with large datasets and developing ML/AI systems such as: natural language processing, speech/text/image recognition, supervised and unsupervised learning models, forecasting and/or econometric time series models
    Developed efficient and effective solutions to diverse and complex business problems
    Technical team leadership experience.
    Experience in Scaled Agile framework is preferred.
    Proactive and action oriented
    Ability to collaborate with, and present to internal and external partners
    Experience in the retail industry or in a production/service environment is preferred.

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