Data Science Manager, Auto Finance Credit Strategy Apply
Location: TORONTO, Ontario, Canada
Time Type: Full time
Posted On: Posted 2 Days Ago
Time Left to Apply: End Date: November 16, 2024 (8 days left to apply)
Job Requisition ID: R-0000103386
Job Summary
As a data specialist on the Portfolio Management & Credit Strategy team, you will analyze, design and implement solutions to enable real-time decision making for the Auto Finance business. The team specializes in leveraging large data sets to generate new insights and make fact-based decisions on how to profitably grow loan originations by balancing risk, pricing, operational efficiency, and customer impact. The role employs a range of leading-edge technologies and capabilities, applying machine learning and statistical techniques, to build predictive behavioral models and credit strategies.
Job Description
What will you do?
Analyze data using empirical, statistical and machine learning techniques to identify problems and uncover actionable insights to improve financial outcomes.
Design automated strategies to improve real-time adjudication and the quality and consistency of manual adjudication.
Engage cross-functional stakeholders across Product, Sales, Operations and Risk Management.
End-to-end project management, from idea conception, solution design, stakeholder buy-in to implementation and monitoring.
Present quarterly, monthly and ad-hoc insights to senior management on acquisitions and portfolio performance.
Maintain and update the in-house built credit decision engine by making code changes in Python, followed by the full release delivery testing process.
What do you need to succeed?
Must-have:
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Behavioral Economics, Engineering, or other quantitative field of study.
2+ years of industry experience in data analytics and/or risk management.
2+ years of experience with programming and scripting languages such as SQL, Python and R.
Strong analytical, problem solving, communication and time management skills.
Familiar with data extract, transform, and load processes with a variety of data types.
Experience with GitHub functionality and code management best practices.
Experience with Linux environment and shell scripting.
Familiar with Apache Spark, Hadoop and Public Cloud technologies, data serialization (JSON, Parquet, etc).
Nice-to-have:
Familiar with credit risk concepts.
Proficiency with OOP and OOD, experience with Java.
Proficiency with data visualization tools such as Tableau.
Experience applying statistical concepts including but not limited to: linear and logistic models, gradient boosting/XGboost, supervised statistical learning, clustering, recommendation systems, times-series analysis, experimental design (A/B testing).
What’s in it for you?
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
Leaders who support your development through coaching and managing opportunities.
Ability to make a difference and lasting impact.
Work in a dynamic, collaborative, progressive, and high-performing team.
A world-class training program in financial services.
Flexible work/life balance options.
Opportunities to do challenging work.
Job Skills
Business Data Analysis, Communication, Credit Analysis, Critical Thinking, Database Queries, Data Visualization, Decision Making, Quantitative Methods, Risk Management
Additional Job Details
Address: WATERPARK PLACE, 20 BAY ST:TORONTO
City: TORONTO
Country: Canada
Work hours/week: 37.5
Employment Type: Full time
Platform: GROUP RISK MANAGEMENT
Job Type: Regular
Pay Type: Salaried
Posted Date: 2024-11-04
Application Deadline: 2024-11-16
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above.
Inclusion and Equal Opportunity Employment
At RBC, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work. We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities.
We also strive to provide an accessible candidate experience for our prospective employees with different abilities. Please let us know if you need any accommodations during the recruitment process.
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