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About the Role

The Data Science Analyst leverages data science, machine learning, and advanced analytics to solve complex business problems within Supply Chain and Operations. This role bridges data, technology, and business operations to create predictive insights, analytical models, and decision-support tools that enhance planning, efficiency, cost management, and service performance.

Responsibilities

• Develop, test, and validate predictive models and machine learning solutions for Supply Chain and Operations use cases.
• Apply statistical modeling, forecasting, classification, regression, clustering, optimization, and other data science techniques to solve business problems.
• Support use cases such as demand forecasting, labor forecasting, inventory risk, transportation optimization, order volume prediction, customer behavior trends, productivity analysis, and operational exception detection.
• Develop and deploy anomaly detection models to identify operational exceptions, service disruptions, inventory irregularities, equipment failures, process deviations, and emerging business risks.
• Support transportation and logistics optimization initiatives by applying advanced analytics and machine learning techniques.
• Clean, transform, structure, and analyze large datasets from multiple business systems.
• Perform exploratory data analysis to identify relationships, trends, anomalies, and improvement opportunities.
• Collaborate with business stakeholders to understand operational processes, pain points, and decision-making needs.
• Translate business problems into data science questions, analytical methods, and measurable outcomes.
• Evaluate model accuracy, performance, stability, and business value.
• Partner with data engineering and IT teams to access, prepare, and improve data sources.
• Create dashboards, visualizations, and presentations to communicate model outputs and recommendations.
• Document model logic, assumptions, data sources, limitations, and business applications.
• Support the deployment, monitoring, and ongoing refinement of analytical and machine learning solutions.
• Stay current on data science, machine learning, AI, and analytics methods that may benefit the business.
• Perform other duties as assigned.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, Economics, Operations Research, Supply Chain, or a related field required.
• Master’s degree in Data Science, Analytics, Statistics, Operations Research, Computer Science, Industrial Engineering, or related discipline preferred.
• 2-5 years of experience in data science, analytics, statistical modeling, machine learning, business intelligence, or related analytical roles.
• Experience applying data science methods to real-world business or operational problems.
• Experience building predictive models, forecasts, or machine learning prototypes preferred.
• Proficiency in Python, R, SQL, or similar analytical programming languages.
• Familiarity with machine learning libraries and methods such as scikit-learn, pandas, NumPy, regression models, classification models, clustering, time series forecasting, or optimization techniques.
• Strong understanding of statistics, probability, data modeling, feature engineering, and model evaluation.
• Ability to work with structured and unstructured data from multiple systems.
• Experience with Power BI, Tableau, Databricks, Azure Machine Learning, Snowflake, or similar platforms preferred.
• Ability to explain technical concepts to non-technical business stakeholders.
• Strong problem-solving, critical thinking, and analytical reasoning skills.
• Strong communication and data storytelling skills.
• Ability to balance technical depth with practical business applications.
• Strong attention to detail, data quality, and model reliability.
• Must be flexible and willing to work the demands of the department which is generally limited to weekdays but may be subject to evenings or weekends due to project or department needs.

Skills

• Data Science
• Machine Learning
• Statistical Modeling
• Advanced Analytics
• Python
• R
• SQL
• Scikit-learn
• Pandas
• NumPy
• Regression Models
• Classification Models
• Clustering
• Time Series Forecasting
• Optimization Techniques
• Power BI
• Tableau
• Databricks
• Azure Machine Learning
• Snowflake
• Data Storytelling

Experience Level

• 2-5 years of experience

Education Level

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, Economics, Operations Research, Supply Chain, or a related field
• Master’s degree in Data Science, Analytics, Statistics, Operations Research, Computer Science, Industrial Engineering, or related discipline preferred

Benefits

• Majority of health insurance paid by Shamrock Foods
• 401(k) Savings Plan
• Profit Sharing
• Paid Time Off
• Growth opportunities
• Continued education
• Wellness programs

About the Company

• At Shamrock Foods Company, people come first – our associates, our customers, and the families we serve across the nation.
• A privately-held, family-owned and -operated Forbes 500 company, Shamrock is an innovator in the food industry and has been since being founded in Arizona in 1922.
• Our Mission: At Shamrock Foods Company, we live by our founding family’s motto to “treat associates like family and customers like friends.”

Equal Opportunity

• At Shamrock Foods Co all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status, sexual orientation, gender identity or any other basis protected by applicable law.
• Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
• This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.