Data Analysis Engineer II

Position Summary

Headquartered in Englewood Cliffs, N.J., Samsung Electronics America, Inc. (SEA), the U.S. Sales and Marketing subsidiary, is a leader in mobile technologies, consumer electronics, home appliances, enterprise solutions and networks systems. For more than four decades, Samsung has driven innovation, economic growth and workforce opportunity across the United States-investing over $100 billion and employing more than 20,000 people nationwide. By integrating our large portfolio of products, services and AI technology, we're creating smarter, sustainable and more connected experiences that empower people to live better. SEA is a wholly owned subsidiary of Samsung Electronics Co., Ltd.
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Role and Responsibilities

Role & responsibilities include:

• Own and manage the operationally critical forecasting tools and processes using internal tools & data, ML modeling to improve the forecast accuracy
• Monitor forecast accuracy, investigate variances, and drive improvements in our predictive forecasting capabilities
• Create and maintain robust logical and physical data models for the data warehouse and business intelligence systems
• Develop interactive dashboards and automated reports to monitor KPIs, reconciliations, new product launches and empower cross-functional teams to make data-driven decisions
• Collect, clean, and analyze complex datasets from various teams, data sources to identify trends and patterns to drive strategic business decisions and growth
• Collaborate with internal & external cross-functional teams like category, engineering, supply chain, sales teams for BOPIS+ and omnichannel operations

Skills and Qualifications

Minimum Qualifications:

• Designing, developing, and maintaining automated data pipelines using Apache Airflow to extract, transform, and load large-scale data from enterprise systems including POS, OMS, CRM, and inventory platforms.
• Developing complex SQL models in Vertica to perform data aggregation, transformation, and feature engineering supporting forecasting and operational reporting
• Building and maintaining time-series forecasting and regression models using Python (SARIMAX, Prophet, Multivariate Regression) to predict product demand, store performance, and inventory movement
• Deploying and managing data infrastructure on AWS (S3, EC2, Redshift) to ensure scalability, reliability, and high availability of analytical workflows
• Creating and managing BI dashboards and visualization tools for executive monitoring of revenue, forecast accuracy, promotion lift, and BOPIS/BOSFS program performance metrics
• Owning BOPIS monthly target planning (quantity and revenue) by coordinating with Samsung account management teams and external BOPIS retail partners to establish, validate, and track performance against monthly sales and volume targets
• Performing data validation, anomaly detection, and exploratory analysis to enhance forecast accuracy and operational efficiency
• Collaborate with internal & external cross category and functional teams such as category, engineering, supply chain, sales teams for BOPIS+ and omnichannel operations
• Must be proficient in SQL, Python, Cloud based data management and modeling
• Must have 3+ years of experience as data analysis engineer, business intelligence engineer, or equivalent positions
• Master's degree or equivalent experience in Computer Science, Statistics, Business Intelligence and Analytics, Engineering Management or a related field

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The salary range for this role is expected to be between $124,000 and $130,500. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.

Regular full-time employees (salaried or hourly) have access to benefits including: Medical, Dental, Vision, Life Insurance, 401(k), Employee Purchase Program, Tuition Assistance (after 6 months), Paid Time Off, Student Loan Program (after 6 months), Wellness Incentives, and many more. In addition, regular full-time employees (salaried or hourly) are eligible for MBO bonus compensation, based on company, division, and individual performance.

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