Sr Specialist, Fraud Data Science

About the Role

Key Responsibilities

• Performs data analytics related to recent fraud trends; leverage advanced analytics to create algorithms to prevent and detect banking fraud
• Responds quickly to analytics requests from Fraud Strategy and Operations, Fraud Intake & Investigations and other stakeholders which might involve creating datasets, performing complex data analyses, developing automated solutions and generating reports
• Manages rules related to Canadian EFT transactions in IBM Safer Payments system
• Operates at a group/enterprise-wide level and serves as a specialist resource to senior leaders and stakeholders
• Uses analysis to provide recommendations and advice for business leaders to maintain market competitiveness, including creating professional level PowerPoint presentations shared with executives and other stakeholders in periodic business meetings
• Applies expertise and thinks creatively to address unique or ambiguous situations and to find solutions to complex and non-routine problems
• Implements changes in response to shifting trends
• Uses advanced analytical algorithms and technologies (e.g., machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights
• Designs and constructs new processes for modeling data
• Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity
• Investigates additional technologies and tools for developing innovative data solutions for business stakeholders
• Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions

Requirements

• Strong knowledge of Banking Fraud
• Advanced degree (Ph.D. preferred) in Computer Science, Mathematics, Physics, Engineering, Statistics, or other quantitative disciplines and/or equivalent experience
• 7+ years of experience with SAS and Python
• Very strong SQL Skills (consideration given to candidates with strong Python skills willing to learn SAS)
• 5+ years of experience with statistical analysis and Machine Learning model development
• Strong verbal and written communication skills
• Tech savviness with the ability to learn new tools and technologies quickly and apply them to solve complex data problems
• Expertise with MS PowerPoint with strong data visualization, influencing and storytelling skills
• Analytical and problem-solving skills with a strong critical thinking ability
• Effective collaboration and team skills with a focus on cross-group collaboration
• Ability to manage ambiguity
• This is a HYBRID role

Nice to Have

• Experience with IBM Safer Payments system
• Experience designing and constructing new data modeling processes
• Experience with developing predictive models using big data technology

Qualifications

• Advanced degree (Ph.D. preferred) in a relevant quantitative discipline or equivalent experience
• 7+ years of experience with SAS and Python
• 5+ years of experience in statistical analysis and machine learning model development

Benefits & Perks

• Salary range of $120,000.00 - $222,600.00, with variation based on location, skills, experience, education, and qualifications
• Performance-based incentives and discretionary bonuses
• Health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans
• Additional perks and rewards as part of BMO's total compensation package
• Supportive work environment with tools and resources for growth, including in-depth training, coaching, manager support, and network-building opportunities