SAS Data Scientist (Mid)

About the Role

We are looking for a SAS Data Scientist to support our client in optimizing demand planning and product sales strategies. This role involves managing monthly forecasting processes, ensuring data integration and accuracy, and collaborating with market demand planners. The ideal candidate will leverage statistical and machine learning methods in SAS to refine forecasts and present insights to senior leadership.

Responsibilities

🔹 Forecasting & Data Integration – Oversee monthly forecasting processes, ensuring high accuracy and seamless integration of multiple data sources.

🔹 Reporting & Validation – Generate and review reports to improve and validate forecasting methods.

🔹 Collaboration with Demand Planners – Work closely with market demand planners to refine and adopt statistical forecasts.

🔹 Machine Learning & Experimentation – Conduct experiments to enhance forecast accuracy and stability.

🔹 Stakeholder Communication – Present forecasting strategies and insights to senior leadership.

🔹 Continuous Improvement – Drive innovation in forecasting techniques, leveraging statistical and machine learning methods.

🔹 Knowledge Sharing – Conduct workshops to share best practices and innovations across regional forecasting teams.

🔹 KPI Monitoring – Track key forecasting metrics and demand trends, adjusting models as needed.

🔹 Ad-Hoc Analysis – Provide on-demand analytical support for client management and demand planning.

Must-Have Skills

✅ Time Series & Predictive Modeling: Strong proficiency in time series forecasting techniques & predictive modeling.

✅ SAS Viya Expertise: Experience with SAS Studio, SAS Model Studio, SAS Environment Manager, SAS Visual Analytics.

✅ SAS 4GL & PROC Steps: Ability to write 4GL Macros, use DATA steps, and PROC steps for statistical modeling (e.g., PROC FORECAST, PROC ARIMA, PROC REG, PROC ESM, PROC HPFDIAGNOSE, PROC SQL).

✅ SQL Proficiency: Experience with Common Table Expressions (CTAS) and advanced SQL queries.

✅ Excel Mastery: Strong skills in conditional statements, logical operators, lookup functions, data validation, pivot tables, and visualizations.

✅ Git Version Control: Ability to branch, checkout, commit, push, merge, and resolve conflicts.

✅ Presentation & Communication: Ability to translate complex analytical insights into business-friendly language.

Nice-to-Have Skills

➕ Understanding of Supply Chain & Demand Planning: Knowledge of inventory control and demand forecasting processes.

➕ Linux Command Line: Experience with process and file management commands.

➕ Power BI & Data Visualization: Familiarity with Power BI for reporting and analysis.

➕ R Programming: Experience with R for statistical analysis and modeling.