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Statistical Developer


Job Title: Statistical Developer
Contract Duration: ASAP - Long term
Languages Required: English
Remote Status: Hybrid
Work Location: Brussels, Belgium
Main skills: R Programming
Experience with SAS
Oracle Database knowledge (SQL, PLSQL)
Statistical Programmer / Data Scientist - Forecasting System Migration
About the Role
We are seeking a skilled Statistical Programmer or Data Scientist to lead the migration of our forecasting system from SAS to R on the Posit platform. This is an excellent opportunity to modernize a critical analytics platform while working with cutting-edge tools and methodologies.
Required Skills
R Programming
Strong proficiency in R for statistical analysis and forecasting
Experience with R packages for time series analysis (forecast, prophet, etc.)
Ability to write clean, efficient, and maintainable R code
SQL
Solid SQL skills for data extraction, transformation, and manipulation
Experience working with relational databases
Ability to optimize queries for performance
Preferred Skills
SAS
Familiarity with SAS programming to understand legacy codebase
Experience translating SAS procedures to R equivalents
Knowledge of SAS forecasting methodologies
Posit Platform
Experience with Posit Workbench, Connect, or Package Manager
Understanding of the Posit ecosystem for enterprise R deployment
Familiarity with RStudio IDE and publishing workflows
Cloud & Data Platforms
Hands-on experience with Databricks for large-scale data processing
Azure cloud platform experience
Understanding of cloud-based analytics architectures
Modern Development Practices
AI/ML model development and deployment
DevOps practices and tooling
Git version control
CI/CD pipeline implementation
Agile/Scrum methodologies
Responsibilities
Translate existing SAS forecasting models and workflows to R
Deploy solutions on the Posit platform
Collaborate with stakeholders to ensure business continuity during migration
Optimize and modernize forecasting processes
Document code and create knowledge transfer materials
Implement best practices for version control and code deployment

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