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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. The analyst collaborates with business leaders and stakeholders to identify use cases, build models, and translate technical findings into actionable business recommendations, suitable for those with strong technical skills and a passion for operational challenges.

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.
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
Predictive Modeling
Forecasting
Classification
Regression
Clustering
Optimization
Anomaly Detection
Exploratory Data Analysis
Data Visualization
Data Storytelling
Python
R
SQL
scikit-learn
pandas
NumPy
Power BI
Tableau
Databricks
Azure Machine Learning
Snowflake

Location

Arizona

Work Type

Full-time

Experience Level

2-5 years

Education Level

Bachelor's degree
Master's degree 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

Shamrock Foods Company is a privately-held, family-owned and-operated Forbes 500 company, founded in Arizona in 1922. They are an innovator in the food industry.
Mission: 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.