JOB DESCRIPTION

Position Title: Senior Data Scientist, Liability Modeling

LOB: Business Analytics & Insights

Duration: 12 months

Possibility of extension: Yes

Possibility of FTE: Yes

Working Location: Hybrid in downtown Toronto ON (1-2 days/wk in office, Team typically goes in on Mondays)

Role Mandate: The incumbent will support Senior Manager, Research and Data Science in developing liability forecasting models for different loyalty programs. They will use advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large data sets, to model behavioral patterns and to produce robust predictions and forecasts for financial planning and to ensure effective management and stability of the loyalty and partner programs. This role closely collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.

Role Responsibilities Include (but are not limited to):

• Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data.

• Designs and implement advanced projection models focused on ultimate redemption rate estimates and overall liability estimates.

• Develops rewards program liability estimation models, including sensitivity impact models and measuring the impact of program changes or redesign.

• Develops customer behavior analyses that allow a program to target more profitable members and increase overall program effectiveness, using advanced predictive models.

• Works independently on end-to-end development of Machine Learning and time series forecasting models to derive insights

• Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.

• Collaborate together with the product team and partners to understand and provide data-driven decision making

• Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.

• Provides specialized consulting, analytical and technical support.

• Exercises judgment to identify, diagnose, and solve problems within given rules.

• Works independently and regularly handles non-routine situations.

• Broader work or accountabilities may be assigned as needed.

Must-Have Skills:

Intermediate level of proficiency:

• Mathematics, statistics & operations research.

• Deep learning.

• Machine learning.

• Trust, bias and ethics.

• Creative thinking.

• Critical thinking.

• CFA, CMA, or FSA is a plus

• Knowledge of financial modeling is a plus

• Knowledge of financial data modelling vs FI product data modelling is preferred

• Actuarial background an asset

• Banking experience is ideal

Advanced level of proficiency:

• Big data.

• Data visualization.

• Computational thinking and programming.

• Data wrangling.

• Data preprocessing.

• Creative reasoning.

• Verbal & written communication skills.

• Collaboration & team skills.

• Analytical and problem-solving skills.

• Influence skills.

• Data driven decision making.

• Expert knowledge of Python and/or SAS

• 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.

• Deep knowledge and technical proficiency gained through extensive education and business experience.

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