Asks for

The ad says“Working knowledge of Agile/SCRUM methodologies with 1-2 years of experience and a practical understanding of the epics, features, and tasks that may be most relevant and how much effort is required for them”
The ad says“Working knowledge of how APIs work, CI/CD (Continuous Integration/Continuous Deployment)”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“1+ years of writing production-grade code in scripting languages including Bash, Python, and SQL with the ability to identify the areas of improvement, optimal choice of data structures, optimization of the code, and creating custom code to address unique situations”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Working knowledge of how APIs work, CI/CD (Continuous Integration/Continuous Deployment)”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“At least 1+ years of working with a major cloud platform, creating ML models using frameworks from data exploration to deployment”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Effective skills in creating, deploying, and troubleshooting containers in the context of ML modeling”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Understanding of DevOps and MLOps principles”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“1+ years of experience with version control systems/concepts, such as Git, for tracking changes in machine learning projects”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Understanding of DevOps and MLOps principles”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“1+ years of writing production-grade code in scripting languages including Bash, Python, and SQL with the ability to identify the areas of improvement, optimal choice of data structures, optimization of the code, and creating custom code to address unique situations”
The ad says“Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more”
The ad says“Working knowledge of Agile/SCRUM methodologies with 1-2 years of experience and a practical understanding of the epics, features, and tasks that may be most relevant and how much effort is required for them”
The ad says“1+ years of writing production-grade code in scripting languages including Bash, Python, and SQL with the ability to identify the areas of improvement, optimal choice of data structures, optimization of the code, and creating custom code to address unique situations”

ARE YOU A CURRENT US FOODS EMPLOYEE? PLEASE APPLY DIRECTLY THROUGH OUR INTERNAL WORKDAY CAREER SITE

Join Our Community of Food People!

The Sr Data Scientist executes statistical and mathematical analyses to support business decision-making. This role supports artificial intelligence/machine learning (AI/ML) in a deployed production environment. They are experts in the field of Data Science. Consequently, the Sr Data Scientist proactively works with cross-functional teams to seek and understand the business/domain context of potential problems that may be solved using ML. They present data science solutions to stakeholders in an iterative fashion. The Sr. Data Scientist works with Associate Data Scientists and Data Scientists in converting a business problem into an ML problem and kickstarting foundational work including data exploration, feature engineering, basic hypothesis testing, and creation of baseline models. They create the model feasibility document in close collaboration with the Data Scientists and Sr Data Scientists. The Sr Data Scientist may have direct reports including Associate Data Scientists and Data Scientists.

The work for the Sr Data Scientist position is completely remote anywhere in the United States except Hawaii or United States Territories.

RESPONSIBILITIES

As a Sr Data Scientist, you will be expected to:

Work with Associate Data Scientists and Data Scientists in researching data sources, data cleansing, feature engineering, and creating baseline models
Independently manage multiple data science model development/projects
Collaborate and engage with various cross-functional stakeholders to ensure close coordination between data science and business stakeholders including the product management team
Provide full ownership of the model development from inception to implementation including the machine learning pipeline, documentation, model drift, and remodeling strategy
Mentor the Associate Data Scientists and Data Scientists in data science knowledge and their interactions with other stakeholders
Coordinate with the ML team, anticipating deployment issues upfront, setting the stage for resource requirements, and ensuring the success of model deployment and retraining
Take and delegate ownership of critical tickets or issues faced by business stakeholders as assigned by the Lead Data Scientist or Director of Data Science
Read and independently navigate through extensive codebase with a focus on troubleshooting, debugging, and/or improvement of code
Contribute to coding standards and coding conventions and proactively participate in enforcing sound coding practices across the data science team
Create and maintain documentation of the ML models, data sources, and methodology
Assist in the creation of feasibility documents
Proactively participate in the core team processes including R&D, recommending, and implementing process improvements or new methodologies
Share knowledge with other various teams and members by presentation at periodic internal team sessions/workshops
Guide usage of development methodologies (Scrum, Kanban, etc.) and assist in their implementation in the group projects by deciphering details including features, tasks, estimates of efforts and timing, etc.

SUPERVISION:

RELATIONSHIPS

Internal: Associate Data Scientists, Data Scientists, Lead Data Scientists, Principal Data Scientists, and Director of DS.

WORK ENVIRONMENT

Remote

MINIMUM QUALIFICATIONS

As a Sr. Data Scientist, you have:

Master’s degree in data science/mathematics/CS/statistics or similar field and 3+ years of experience OR Bachelor's degree and 6+ years of experience in data science
Effective written, verbal, and interpersonal communication skills, with the ability to work and communicate effectively with team members and cross-functional teams
An expert-level understanding of the following topics:
- Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more

Working knowledge of Agile/SCRUM methodologies with 1-2 years of experience and a practical understanding of the epics, features, and tasks that may be most relevant and how much effort is required for them
Sufficient intellectual curiosity to investigate the latest developments in the field (for example LLM/Generative AI models)
Ability to see the big picture and anticipate issues in terms of deployment limitations, data latency, appropriateness of a particular implementation of algorithms, and mathematical details/assumptions
At least 1+ years of working with a major cloud platform, creating ML models using frameworks from data exploration to deployment
Working knowledge in handling large datasets in a cloud environment
Working knowledge of how APIs work, CI/CD (Continuous Integration/Continuous Deployment)
Understanding of DevOps and MLOps principles
1+ years of writing production-grade code in scripting languages including Bash, Python, and SQL with the ability to identify the areas of improvement, optimal choice of data structures, optimization of the code, and creating custom code to address unique situations
Proven, independent ability to navigate a data lake environment while creating training datasets or feature stores
Effective skills in creating, deploying, and troubleshooting containers in the context of ML modeling
1+ years of experience with version control systems/concepts, such as Git, for tracking changes in machine learning projects
Ability to investigate/research ML frameworks/algorithms, datasets, feature stores, and contribute to solving data science problems
Capability of providing macro-level thought leadership to the junior members including the Data Scientists regarding best practices, issues, causes, and respective resolutions of those issues

This role may also receive annual incentive plan bonus.

Benefits for this role may include health insurance, pre-tax spending accounts, retirement benefits, paid time off, short-term and long-term disability, employee stock purchase plan, and life insurance. To review available benefits, please click here: https://www.usfoods.com/careers/benefits.html.

Compensation depends on relevant experience and/or education, specific skills, function, geographic location, and other factors as applicable by law (for example: state or local minimum wage thresholds). The expected base rate for this role is between

$100,000 - $155,000

***EOE – Race/Color/Religion/Sex/Sexual Orientation/Gender Identity/National Origin/Age/Genetic Information/Protected Veteran/Disability Status***