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$15.25 - $19.50/hr
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Scottsdale, AZ · Hybrid
$15.25 - $19.50/hr
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Scottsdale, AZ · On-site
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Assistant Economics Data Science information
What is the difference between Assistant Economics Data Science vs Data Analyst?
| Aspect | Assistant Economics Data Science | Data Analyst |
|---|---|---|
| Required Credentials | Bachelor's in Economics, Data Science, or related field; some roles prefer certifications in data analysis or programming | Bachelor's in Statistics, Mathematics, or related field; certifications in data analysis tools are common |
| Work Environment | Research-focused, often in economic or policy institutions, government agencies, or consulting firms | Business environments, corporate offices, or consulting firms analyzing data to inform decisions |
| Employer & Industry Usage | Used in economic research, policy analysis, and academia | Used across industries like finance, marketing, healthcare, and technology |
While both roles involve data analysis, Assistant Economics Data Science focuses on economic data and policy research, often requiring economic knowledge. Data Analysts work across various industries analyzing diverse datasets to support business decisions. The roles share skills in data handling and analysis but differ in focus and application.

Full-time
Medical, Retirement, PTO
Posted 9 days ago
Shamrock Foods rating
8.1
Based on 49 frontline employees who took The Breakroom Quiz
9th of 49 rated food wholesalers
Job description
The Data Science Analyst is responsible for using data science, machine learning, statistical modeling, and advanced analytics to solve complex business problems across Supply Chain and Operations. This role works at the intersection of data, technology, and business operations to develop predictive insights, analytical models, and decision-support tools that improve planning, efficiency, cost management, and service performance.
The Data Science Analyst partners with business leaders, operations teams, IT, data engineering, and analytics stakeholders to identify high-value use cases, build and test analytical models, and translate technical outputs into actionable business recommendations. This role is well suited for a candidate who has strong technical skills but also enjoys applying those skills to practical operational challenges.
Essential Duties:
- 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 before they impact performance.
- Support transportation and logistics optimization initiatives by applying advanced analytics and machine learning techniques to improve route efficiency, reduce fuel consumption, optimize network flows, and enhance service performance.
- 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.
- Partners with data engineering and IT teams to access, prepare, and improve data sources needed for modeling and analysis.
- 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.
- Other duties as assigned.
Qualifications:
- 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.
Corporate Summary:
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.”
Why work for us?
Benefits are a major part of your overall compensation, and we believe offering them at an affordable cost is not only the right thing to do, but it helps keep you and your family healthy. That’s why Shamrock Foods pays for the majority of your health insurance, allowing you to take home more of your paycheck. And it doesn’t stop there - our associates also enjoy additional benefits such as 401(k) Savings Plan, Profit Sharing, Paid Time Off, as well as our incredible growth opportunities, continued education, and wellness programs.
Equal Opportunity Employer
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.
What Shamrock Foods employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Shamrock Foods
Sourced by ZipRecruiter
Industry
Food services and drinking places
Company size
5,001 - 10,000 Employees
Headquarters location
Phoenix, AZ, US
Year founded
1922