Data Science Analyst
On-sitePhoenix, Arizona, United States
Job Summary
Develop, test, and validate predictive models and machine learning solutions for Supply Chain and Operations use cases, including demand forecasting, inventory risk, and transportation optimization. Apply statistical modeling, forecasting, classification, regression, and clustering techniques to solve business problems while cleaning and transforming large datasets from multiple systems. Collaborate with business leaders, operations teams, and IT stakeholders to identify high-value use cases, translate technical outputs into actionable recommendations, and create dashboards to communicate model outputs. Evaluate model accuracy and performance, document logic and assumptions, and support the ongoing deployment and refinement of analytical solutions. Stay current on data science and AI methods to improve planning, efficiency, and service performance. Must be flexible to work evenings or weekends as needed for department demands.
Required Qualifications
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, Economics, Operations Research, Supply Chain, or a related field
- 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
- Proficiency in Python, R, SQL, or similar analytical programming languages
- Strong understanding of statistics, probability, data modeling, feature engineering, and model evaluation
- Ability to work with structured and unstructured data from multiple systems
- 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
Desired Qualifications
- Master's degree in Data Science, Analytics, Statistics, Operations Research, Computer Science, Industrial Engineering, or related discipline
- Experience building predictive models, forecasts, or machine learning prototypes
- Familiarity with machine learning libraries and methods such as scikit-learn, pandas, NumPy, regression models, classification models, clustering, time series forecasting, or optimization techniques
- Experience with Power BI, Tableau, Databricks, Azure Machine Learning, Snowflake, or similar platforms
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