Data Engineer, Fraud Predictive Analytics

Address: 100 King Street West

Job Family Group:
Data Analytics & Reporting

Hybrid role

• Applies knowledge of advanced analytic algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to deliver better prediction models and/or intelligent automation that enables smarter business decisions, improved customer experience, and drives productivity.
• Applies strong communication and story-telling skills to summarize statistical/algorithmic findings, draw business conclusions, and present actionable insight in a way that resonates with business/groups.
• Drives innovation through the development of Data & AI products that can be leveraged across Financial Crimes Unit to build advanced fraud detection, fraud investigation, fraud prevention tools/models.
• Conducts research to identify, assess and recommend viable, practical solutions to specific financial crimes /criminal risk exposures.
• Develops and maintains an understanding of the financial crime management processes, frameworks and techniques.
• Recommends and implements solutions based on analysis of issues and implications for the business.
• Understands and analyzes complex business problem, then formulates data-driven hypotheses to drive business value.
• Builds effective relationships with internal/external stakeholders and ensures alignment.
• Supports data collection, integration, and retention requirements for data.
• Defines innovative data solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
• Diagnoses and resolves predictive / analytical model performance issues while monitoring system performance and implementation of efficiency improvements.
• Develops analytical solutions and makes recommendations based on an understanding of the business strategy and stakeholder needs.
• Works with various data owners to discover and select available data from internal sources and external vendors (e.g. financial crime data) to fulfill analytical needs.
• Applies scripting / programming skills to assemble various types of source data (unstructured, semi-structured, and structured) into well-prepared datasets with multiple levels of granularities (e.g., demographics, customers, products, transactions).
• Develops agreed analytical solution by applying suitable statistical & machine learning techniques (e.g., A/B testing, prototype solutions, mathematical models, algorithms, machine learning, deep learning, artificial intelligence) to test, verify, refine hypotheses.
• Uses the appropriate algorithms to discover patterns.
• Supports development of tools and delivers training for data analytics and AI.
• Broader work or accountabilities may be assigned as needed.

• Typically between 5 - 7 years of relevant experience in Data Science & Analytics and post-secondary degree in related field of study or an equivalent combination of education and experience.
• Advanced degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or other quantitative disciplines and/or equivalent experience.
• Experience with programming languages (e.g. SQL, Python, PySpark) and machine learning /deep learning algorithms/packages (e.g. XGBoost, H2O, SparkML).
• Deep proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
• Experience building fraud models (investigation, detection, prevention) for a large Financial Institution.

Salary: $80,000.00 - $

Pay Type:

Salaried

• BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.

To view more details of our benefits, please visit:

At BMO we are driven by a shared

Purpose:

Boldly Grow…