SAS Data Scientist - Mid @ Link Group

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.

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 .

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.

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.] Requirements : Forecasting, SAS, CTAS, SQL, Excel, Git, Linux, Power BI, Data visualization, R Tools : Agile, Scrum.