Data Scientist - SAS to Python Migration (AI/ML, AWS)

Job Title:

Data Scientist – SAS to Python Migration (AI/GenAI, AWS)

Location:

Toronto, ON (Hybrid – 4 Days Work From Office)

Job Summary

We are seeking an experienced Data Scientist to lead the conversion of legacy SAS codebases to Python using generative and agentic AI tools. This role involves analyzing existing SAS programs, interpreting business logic and statistical methods, and ensuring accurate, validated Python equivalents. You will play a key role in modernizing legacy systems while maintaining data integrity and regulatory alignment.

Key Responsibilities

• Analyze and interpret existing SAS programs, including business logic, statistical methods, and data transformations
  
• Leverage agentic AI tools to convert SAS code into accurate, well-tested Python code
  
• Conduct thorough code reviews of AI-generated outputs to ensure correctness and alignment with business requirements
  
• Perform numerical validation by comparing Python outputs with original SAS results
  
• Document conversion logic, statistical equivalencies, and any deviations from original implementations
  
• Identify ambiguities in legacy SAS code and escalate to business or model owners as needed
  
• Collaborate with data platform engineers within a shared migration framework
  
• Provide inputs and requirements to enhance migration frameworks and tooling
  

Required Qualifications

• Minimum 3+ years of experience in data science
  
• Strong proficiency in SAS , including:
  • Base SAS
    
  • PROC SQL
    
  • SAS Macros
    
  • SAS/STAT, SAS/ETS
    
  • SAS Enterprise Guide
    
• Strong proficiency in Python for data science and modeling:
  • pandas
    
  • numpy
    
  • scikit-learn
    
  • statsmodels
    
  • scipy
    
• Experience with SQL and working with cloud-based or remote data systems
  
• Familiarity with AWS services (e.g., S3) or similar cloud platforms
  
• Experience with Git for version control
  
• Hands-on experience with AI coding assistants / LLM tools (e.g., GitHub Copilot, Claude)
  
• Strong analytical, problem-solving, and documentation skills
  

Preferred Qualifications

• Experience in regulated or enterprise environments (banking, finance, insurance, pharma, government)
  
• Experience working in a UNIX/Linux environment
  
• Familiarity with credit risk models , including:
  • Probability of Default (PD)
    
  • Exposure at Default (EAD)
    
  • Loss Given Default (LGD)
    
• Understanding of IFRS9 regulatory requirements
  

Technical Skills

• SAS (Base, Macros, PROC SQL, SAS/STAT, SAS/ETS)
  
• Python (pandas, numpy, scikit-learn, statsmodels, scipy)
  
• SQL & relational databases
  
• Cloud platforms (AWS preferred)
  
• Git (version control)
  
• AI/GenAI tools for code generation and automation
  

Additional Information

• Opportunity to work on large-scale legacy modernization initiatives
  
• Exposure to cutting-edge AI-driven development tools
  
• Collaborative environment with data engineers and business stakeholders
  
• High-impact role within a financial services domain