62353-1 - Sr Data Scientist working with Python and SAS to mine and analyze large data sets and financial models utilizing machine learning for a banking

Position Title: Sr. Data Scientist, Liability Modeling

LOB: Business Analytics & Insights

Duration: 12 months with possible extension

Working Location: Hybrid (1-2 days/wk in DT Toronto 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.

Must-Have Skills:

• 5 - 7 years of relevant experience as Data Scientist performing data analysis, data visualization, data wrangling and data preprocessing
• Machine learning/ML and Big Data experience
• Expert knowledge of Python and/or SAS
• Experience performing financial modelling
• Banking experience

Nice to haves:

• Financial data modelling vs FI product data modelling is preferred

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 the bank; 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.

Interview Process:

First Round - 45 Teams meeting with HM and Senior Team Member