Data Scientist

The foodservice professional’s premier source for restaurant equipment, supplies, and knowledge online. Our purpose is to empower and equip people to run their businesses more profitably and efficiently.
Webstaurant Store, the world’s largest online restaurant supply company, is looking for a full-time Applied Data Scientist to join the Business Intelligence and Data Warehousing team. The role will be responsible for applying enhanced predictive analytics, machine learning, and artificial intelligence techniques to the reporting and data discovery needs of departments across the organization. These data-driven solutions are targeted on the Azure cloud platform and/or our inhouse Nvidia Triton LLM server, and will focus on supply chain, sales, warehouse, and call center efficiency.
This role can be remote (See below for remote work requirements) or based in one of our offices (Lititz, PA or Tampa, FL).
Responsibilities include, but are not limited to:
Analyzing the demand and supply patterns of various restaurant products and services using Machine Learning and other data science tools.
Developing and deploying predictive models to optimize inventory management, delivery routes, pricing strategies, and customer satisfaction.
Creating and maintaining data pipelines to ingest, process, and transform data from various sources, such as point-of-sale systems, online orders, customer feedback, and market research.
Collaborating with business analysts, data engineers, and other stakeholders to understand the business objectives and requirements, and to communicate the insights and recommendations from data analysis.
Evaluating and testing the performance, accuracy, and reliability of the machine learning models, and updating them as needed to reflect changing data and business conditions.
Exploring new data sources and methods to enhance the data quality and quantity, and to generate new insights and opportunities for the business.
Having an expertise level using data visualization tools for creating and presenting high-quality reports, dashboards, and visualizations to showcase the results and impacts of the data science projects, and to provide actionable insights for decision making.
The ideal candidate will possess the following qualities:
Proficiency in data analysis, machine learning, and statistical techniques, such as data mining, data modeling, predictive modeling, data visualization, etc.
Experience in using Microsoft Azure’s tools and services for data science and machine learning, such as Azure Machine Learning, Azure Databricks, Azure Data Factory, etc.
Knowledge of Python libraries and frameworks for data science and machine learning, such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc.
Knowledge of Hadoop and GitHub
Knowledge with GPU hardware, CUDA, or Nvidia Triton
Understanding of different algorithms, such as logistic regression, decision trees, convolutional neural networks, etc.
Ability to design and implement machine learning experiments, train ML models, and deploy and monitor scalable machine learning solutions
Ability to collaborate with other data professionals and stakeholders to understand the business objectives and requirements, and to communicate the insights and recommendations from data analysis
Excellent business acumen and domain knowledge in inventory management, logistics, or fraud prevention
Advanced math and statistics skills
Critical thinking and problem-solving skills
The ability to work both independently and within a team
Possess an entrepreneurial spirit, with a humble attitude in both supporting your own ideas and accepting the ideas and viewpoints of others
Job Description Job Summary:
Webstaurant Store, the world’s largest online restaurant supply company, is looking for a full-time Applied Data Scientist to join the Business Intelligence and Data Warehousing team. The role will be responsible for applying enhanced predictive analytics, machine learning, and artificial intelligence techniques to the reporting and data discovery needs of departments across the organization. These data-driven solutions are targeted on the Azure cloud platform and/or our inhouse Nvidia Triton LLM server, and will focus on supply chain, sales, warehouse, and call center efficiency.
This role can be remote (See below for remote work requirements) or based in one of our offices (Lititz, PA or Tampa, FL).
Responsibilities include, but are not limited to:
Analyzing the demand and supply patterns of various restaurant products and services using Machine Learning and other data science tools.
Developing and deploying predictive models to optimize inventory management, delivery routes, pricing strategies, and customer satisfaction.
Creating and maintaining data pipelines to ingest, process, and transform data from various sources, such as point-of-sale systems, online orders, customer feedback, and market research.
Collaborating with business analysts, data engineers, and other stakeholders to understand the business objectives and requirements, and to communicate the insights and recommendations from data analysis.
Evaluating and testing the performance, accuracy, and reliability of the machine learning models, and updating them as needed to reflect changing data and business conditions.
Exploring new data sources and methods to enhance the data quality and quantity, and to generate new insights and opportunities for the business.
Having an expertise level using data visualization tools for creating and presenting high-quality reports, dashboards, and visualizations to showcase the results and impacts of the data science projects, and to provide actionable insights for decision making.
The ideal candidate will possess the following qualities:
Proficiency in data analysis, machine learning, and statistical techniques, such as data mining, data modeling, predictive modeling, data visualization, etc.
Experience in using Microsoft Azure’s tools and services for data science and machine learning, such as Azure Machine Learning, Azure Databricks, Azure Data Factory, etc.
Knowledge of Python libraries and frameworks for data science and machine learning, such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc.
Knowledge of Hadoop and GitHub
Knowledge with GPU hardware, CUDA, or Nvidia Triton
Understanding of different algorithms, such as logistic regression, decision trees, convolutional neural networks, etc.
Ability to design and implement machine learning experiments, train ML models, and deploy and monitor scalable machine learning solutions
Ability to collaborate with other data professionals and stakeholders to understand the business objectives and requirements, and to communicate the insights and recommendations from data analysis
Excellent business acumen and domain knowledge in inventory management, logistics, or fraud prevention
Advanced math and statistics skills
Critical thinking and problem-solving skills
The ability to work both independently and within a team
Possess an entrepreneurial spirit, with a humble attitude in both supporting your own ideas and accepting the ideas and viewpoints of others

Remote work qualifications

Access to a reliable and secure high-speed internet connection. Cable or fiber internet connections (at least 75mbps download/10mbps upload) are preferred, as satellite connections often cannot support the technologies used to perform day-to-day tasks.
Access to a home router and modem.
A dedicated home office space that is noise- and distraction-free. The space should have strong wireless connection or a wired Ethernet connection (wired connection is preferred, if possible).
A valid, physical address (apartment, suite, etc.). PO Boxes are not supported, as a physical address is required for you to receive your computer equipment.
The desire and ability to work and communicate with other team members via chat, webcam, etc.
Legal residents of one of the following states: (AK, AL, AR, AZ, CT, DE, FL, GA, IA, ID, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, NC, ND, NH, NM, NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, VT, WI, WV, and WY). H-1B Visa Sponsorship Not Available, W2 only.

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