Data Scientist, SAS-to-Python Migration

Infotek Consulting Inc.; Toronto; Hybrid; CAD 110,000 - 131,000; Full time

Job summary

Infotek Consulting Inc. in Toronto seeks a Data Scientist Expert to drive the SAS-to-Python migration for IFRS9 modeling and risk analytics. You will translate legacy SAS scripts into Python and optimize for performance within a modern Python-based ecosystem.

Responsibilities include parallel validation, data mining and modeling, data lineage creation, and training staff to sustain the new platform. A strong SAS/Python background and 10+ years in migration are essential.

Qualifications

• 10+ years of SAS migration and data migration experience, preferably from financial institutions.
• Advanced SAS and Python expertise with proven SAS-to-Python migration experience.
• Proficiency in data profiling, validation, and quality assurance.

Responsibilities

• Translate SAS scripts into Python for IFRS9 and risk analytics ensuring functional equivalence.
• Run parallel SAS and Python processes to verify outputs and reduce transition risk.
• Use advanced data mining and statistical modeling in IFRS9 and credit risk analytics.
• Create data dictionaries and end-to-end data lineage for regulatory compliance and auditability.
• Conduct structured training sessions to transfer knowledge to permanent staff.

Skills

SAS migration for data

Python

IFRS9 modeling

Credit risk analytics

Data profiling

Data lineage mapping

Parallel testing

Validation

Education

Bachelor’s Degree

Master’s degree in statistics or related

Tools

Python

SAS applications

Job description

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 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.

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