Business Data Analyst (Wholesale Credit Risk)

Role: Business Data Analyst (Wholesale Credit Risk)

Location: Toronto, ON – Hybrid (4 days onsite per week)

Duration: 6 Months (possible extension)

Must-Have Skills: Experience with SQL + Credit Risk/Wholesale data + SAS/Python + Data Testing

Candidate having prior experience with Commercial lending data, Credit risk metrics (PD, LGD, EAD, ratings), SQL and hands-on data experience. Looking for someone with Risk/Finance/Portfolio teams and who has exposure to lending or credit systems.

Reason for hire: supporting data needs and added workload, change management

Provides change management, data services and analysis in support of MDPA

Key Accountabilities:

• Providing subject matter expertise on Wholesale Credit Risk data, data processes and systems
• Assisting in the system development and perform comprehensive testing to ensure technology deliverable fulfill business requirement
• Perform in depth data analysis and investigation.
• Providing tactical solution for urgent business requirement.
• Identifies and documents the business partner’s functional and data requirements based on a business process description or data process to ensure that the final deliverable coincides with the context of the business operations
• Reviews project documents (e.g., High Level Requirements Document [HLRD], High Level System Design Documents [HLSD], and application code) to ensure quality, completeness, and adherence to documentation standards, as well as identifies synergies between initiatives in order ensure the efficiency and effectiveness of the development process

Knowledge & Skills:

• Proficient using SQL statements to query data and perform data profiling, data verifications
• Strong experience with business system analysis in a complex data warehousing environment running on Netezza and Cloud.
• Strong experience gathering business requirement from client groups and converting these into functional specification documents
• Strong sense of commitment
• Experience with SAS/Python
• Background in Data Science, Information Systems, Statistics
• Possesses solid business knowledge in Finance/Banking industry
• Strong analytical skills, communication skills and presentation skills

Education

• Possesses a university degree in Data Science, Engineering, Information Systems and/or Business