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The supply chain data science optimization role will support optimization initiatives through the development of forward-looking analytics, including data exploration, decision modeling, statistics, measurement sciences, and machine learning operations. The main responsibilities include, but are not limited to, developing and productionalizing customized optimization models that enhance supply chain replenishment by balancing a breadth of constraints, variables, and cost considerations. This role requires a deep analytical, technical, and complex problem-solving skill set with expertise in mathematical optimization, statistical analysis, and advanced modeling techniques.
The Data Scientist will collaborate with Decision & Data Scientists to translate business challenges into well-structured optimization or machine learning ML problems. Additionally, they will support foundational efforts such as data exploration, feature engineering, hypothesis testing, and baseline modeling, and play a key role in selecting and implementing the appropriate analytical approach.
This position is remote which means the work can be completed from anywhere in the United States except Hawaii or United States Territories.
Essential Duties And Responsibilities
As a Data Scientist, you will be expected to:
- Collaborate with Decision & Data Scientists in researching data sources, data cleansing, feature engineering, and baseline modeling
- Independently lead the formulation and development of optimization and/or ML models
- Design, implement, and refine mathematical programming models (e.g., Mixed-Integer Linear Programs) to solve large-scale, real-world supply chain problems
- Own the delivery of milestones in the ML development lifecycle
- Assist in delivering complete machine learning-based model solutions from inception to implementation and rollout
- Mentor Associate Data Scientists in data science knowledge and their interactions with other stakeholders
- Share responsibility for the entire code lifecycle
- Read and independently navigate through extensive codebases with a focus on troubleshooting, debugging, and/or improvement
- 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
SUPERVISION:
RELATIONSHIPS
- Internal: Associate Data Scientists, Sr Data Scientists.
WORK ENVIRONMENT
- Inside office
- Internal Associate facing
Minimum Qualifications
As a Data Scientist supporting Supply Chain Optimization, you have:
- A Master’s degree in data science/mathematics/CS/statistics or similar field plus 1+ years of experience OR Bachelor's degree and 3+ years of experience in data science
- 1+ year of Optimization & Operations Research experience
- 1+ years of supply chain analytics experience, preferably in order optimization, network optimization, inventory management, logistics, and/or replenishment
- 1+ years of writing production-grade codes in scripting languages including Bash, Python, and SQL
- 1+ years of experience writing production-grade codes in optimization modeling languages; Gurobi, Pyomo, PuLP, etc
- Practical 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
- Effective written, verbal, and interpersonal communication skills, with the ability to work and communicate effectively with team members and cross-functional teams.
- Working knowledge of Agile/SCRUM methodologies with 1-2 years of experience
- 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
- Proven independent ability to navigate through 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, and feature stores, and contribute to solving data science problems
- Experience in collaborating and engaging with various cross-functional stakeholders
Certifications/Training
Licenses
This role is also eligible for Benefits for this role include annual bonus of up to 15% above base salary, long term incentive, 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 minimum wage thresholds). The expected base rate for this role is between
$75,000 - $120,000
- EOE – Race/Color/Religion/Sex/Sexual Orientation/Gender Identity/National Origin/Age/Genetic Information/Protected Veteran/Disability Status***
