Data Scientist, SAS-to-Python Migration

Actual Job Title: Data Scientist, SAS-to-Python Migration (Expert)

Duration: 8 months (Extension possible)

Location: Toronto (4 days onsite)

Rate: $80-95/h (INC)

Department: Group Risk Management

Department Description

• Working across 2 teams alongside 10 members in total.
• Reports directly to the Hiring Manager.

Daily Responsibilities

• Code Conversion: Translate existing SAS scripts into Python for critical deliverables including IFRS9 Model, Risk Campaigns, and Reporting and Analytics. Ensure logic accuracy and functional equivalence, optimizing code for performance and maintainability in the Python environment.
• Parallel Validation: Execute simultaneous runs of legacy SAS and new Python processes to verify identical outputs and mitigate transition risks.
• Data Mining & Statistical Modeling: Leverage advanced data mining techniques and statistical modeling methodologies to extract, analyze, and validate complex datasets within the IFRS9 and Risk Management domains.
• Data Lineage & Compliance: Create a comprehensive data dictionary and establish end-to-end data lineage, documenting data origin, transformation, and movement throughout its lifecycle to support regulatory compliance and auditability.
• Training and Knowledge Transfer: Conduct structured training sessions with permanent staff to ensure seamless sustainment.

Project Name and Description

• Project Name: CREATE
• Leading the strategic migration of legacy SAS applications to a modern Python-based ecosystem.

Essential Program/Technology/Software Knowledge

• Python
• SAS applications

Must-Have Skills, Experience, Education and Qualifications

• 10+ years of experience in SAS migration and data migration, with preference for candidates from financial institutions.
• Advanced SAS and Python expertise, with proven SAS-to-Python migration experience.
• Proficiency in data profiling, validation, and quality assurance.
• Data lineage mapping and data dictionary development expertise.
• Strong understanding of IFRS9 modeling and credit risk analytics.
• Parallel testing and validation capabilities.

Nice-to-Have Skills, Experience and Qualifications

• Bachelor’s Degree.
• Master’s degree or equivalent in statistical background (strongly preferred).
• Financial institution background is preferred.

Soft Skills

• Excellent technical documentation and communication abilities.
• Proven ability to work with teams and deliver on time.
• Post-conversion support and maintenance capability.

Success Measures

• Successfully converting code within established timelines.
• Effectively handling cross-training programs so team members can perform efficiently.

Note: We use AI tools to: obtain basic information, detect plagiarism, false employment history or references, categorize your skills, and do an initial match with job posting.