What you’ll be doing

As a Consultant, Fraud Analytics, you will independently design and perform moderately complex statistical analysis using advanced analytical techniques and data mining tools to deliver fraud monitoring, detection and prevention solutions by using SAS, SQL and/or Python. Predictive modeling include complex statistical concepts/theories and predictions including optimization, neural nets, logistic regression, decision trees, random forest and sampling. You will also conduct ongoing data analysis associated with rules management within CIBC’s fraud mitigation systems. Thereby, implementing new strategies and continuous improvement to existing strategies, associated with fraud monitoring systems, in order to mitigate fraud losses and decrease customer impacts/irritants. You will also collaborate with internal and external stakeholders to ensure successful deployment of fraud solutions across the bank’s ecosystem.

At CIBC, we enable the work environment most optimal for you to thrive in your role. Details on your work arrangement (proportion of on-site and remote work) will be discussed at the time of your interview.

How you’ll succeed

• Analytical Thinking – Improve fraud monitoring by creatively responding to fraud trends and mitigating risk surrounding new operational processes. Guide strategy by providing evidence based analytical solutions. Conduct considerably complex feasibility studies and cost/benefit analysis to clearly depict possible fraud mitigation rule options and recommended courses of action.  

• Data Management – Creation and maintenance of SAS, SQL, and Python programs to access a decision support data repository.  Database management/querying, and computer programming/software expertise. 

• Communication Skills – Excellent verbal and writing skills to effectively articulate ideas and opinions that involve analysis, interpretation, and assessment. 

Who you are

• You give meaning to data. You enjoy investigating complex problems, and making sense of information. You're confident in your ability to communicate detailed information in an impactful way. You have experience using SAS EG, SAS Miner, Tableau and/or SQL.  

• You have a degree/diploma in analytics, statistics, mathematics, computer science or business management related field. Master’s level degree would be an asset. 

• You demonstrate 5+ years of analytical experience in data science related roles or extensive analytical background related to fraud or risk management.

• You love to learn. You're passionate about growing your knowledge, and you know that there is no limit to what you can achieve. You are current in new modeling and analytical techniques and constantly seek to improve your knowledge in this field. 

• You look beyond the moment. You make decisions and take actions that will make a difference today and tomorrow. You proactively seek new opportunities to define what's possible. You are curious and proactive, you constantly offer new solutions based on sound analysis. 

• Values matter to you. You bring your real self to work and you live our values – trust, teamwork and accountability. 

.

What CIBC Offers

At CIBC, your goals are a priority. We start with your strengths and ambitions as an employee and strive to create opportunities to tap into your potential. We aspire to give you a career, rather than just a paycheck.

• We work to recognize you in meaningful, personalized ways including a competitive salary, incentive pay, banking benefits, a benefits program*, defined benefit pension plan*, an employee share purchase plan, a vacation offering, wellbeing support, and MomentMakers, our social, points-based recognition program.

• Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients.

• We cultivate a culture where you can express your ambition through initiatives like Purpose Day; a paid day off dedicated for you to use to invest in your growth and development.

*Subject to plan and program terms and conditions

Job Location

Employment Type

Weekly Hours

Skills