Consultant, Fraud Analytics

Location: Toronto, Canada — 750 Law Ave. W., E4. Work arrangement details, including the proportion of on-site and remote work, will be discussed during the interview.

Company

CIBC is a relationship-oriented bank developing modern banking services and fraud mitigation solutions.

What you will do

• Design and perform moderately complex statistical analyses using advanced analytical techniques and data-mining tools.
• Develop fraud monitoring, detection, and prevention solutions using SAS, SQL, and Python.
• Build predictive models involving neural networks, logistic regression, decision trees, random forests, optimization, and sampling.
• Analyze data for rules management and implement new strategies to reduce fraud losses and customer impacts.
• Conduct feasibility studies and cost-benefit analyses for fraud mitigation rules.
• Collaborate with internal and external stakeholders to deploy fraud solutions across the bank’s ecosystem.

Requirements

• 5+ years of analytical experience in data science, fraud, or risk management.
• Experience with SAS Enterprise Guide, SAS Miner, Tableau, and/or SQL.
• Strong programming and database management/querying skills using SAS, SQL, and Python.
• Degree or diploma in analytics, statistics, mathematics, computer science, business management, or a related field.
• Strong verbal and written communication skills for presenting analysis, interpretation, and recommendations.
• Legal eligibility to work in Canada and, where applicable, a valid work or study permit.

Nice to have

• Master’s degree in a related field.
• Current knowledge of new modeling and analytical techniques.

Culture & Benefits

• Competitive salary and incentive pay.
• Banking benefits, a benefits program, and a defined benefit pension plan.
• Employee share purchase plan, vacation offering, and wellbeing support.
• Paid Purpose Day for personal growth and development.
• Inclusive and accessible work environment with an emphasis on trust, teamwork, and accountability.

Hiring process

• Potential attribute-based assessment and skills testing, including simulation, coding, or French proficiency assessments.
• Artificial intelligence tools may be used during recruitment.