Senior Manager, Machine Learning Operations Product Owner

RBC; Toronto; On-site; CAD 80,000 - 100,000; Full time

Job summary

A leading financial institution in Toronto is seeking a Senior Manager, Machine Learning Operations Product Owner. In this role, you will lead the deployment of innovative retail credit risk models and strategies using advanced data engineering skills. You will also collaborate closely with data science and engineering teams, ensuring robust and compliant data workflows. The position offers a dynamic work environment emphasizing both technical and strategic contributions to the future of credit analytics.

Benefits

Comprehensive Total Rewards Program including bonuses and flexible benefits

Opportunity to influence credit decisions

Agile, collaborative, high-performing team environment

Qualifications

• 5+ years of experience in financial services, preferably in risk management, credit analytics, or product ownership.
• Hands-on experience with large-scale data management or ETL pipelines.
• Proven experience working across business, data science, and engineering teams.

Responsibilities

• Implement and support models on the IBM Watson platform.
• Build and maintain production-grade data workflows.
• Guide IT implementation team and own product backlog.

Skills

Business Data Analysis

Communication

Credit Analysis

Database Queries

Data Visualization

Decision Making

Long Term Planning

Operational Delivery

Quantitative Methods

Risk Management

Education

Degree in Computer Science, Engineering, Mathematics, Statistics or related field

Tools

Python

SQL

PySpark

IBM Watson

Cloud-based data platforms (e.g., Snowflake, BigQuery)

Job description

Job Description

What is the opportunity?

Join us in shaping the core data and model infrastructure that powers credit decisioning at RBC.

RBC Group Risk Management, Retail Credit Strategies and Modeling Infrastructure team, is hiring a Senior Manager, Machine Learning Operations Product Owner with deep data engineering skills to lead the deployment of next-generation retail credit risk models and strategies. In this role, you’ll sit at the crossroads of data science, engineering, and business strategy—translating complex model logic into scalable, production-ready systems.

You’ll design and optimize end-to-end data pipelines, collaborate with risk and technology teams to deploy models into production, and ensure every solution is accurate, compliant, and built for performance at scale.

If you thrive in bridging technical depth with business impact—this is your chance to make a tangible impact on the future of credit analytics.

Please note this is an in-office role with a minimum of 4 days in office per week.

What will you do?

• Implement and support models on the IBM Watson platform, working closely with IT for seamless integration.
• Build and maintain production-grade data workflows using Python, SQL, and PySpark, addressing data quality, automation, and scalability.
• Optimize code for credit risk models and strategies, troubleshoot and resolve production issues related with data pipelines.
• Guide IT implementation team, own and prioritize the product backlog for deploying risk and credit models and strategies.
• Make decisions on technical details around the ETL and preprocessing solutions, and deployment of models.
• Partner with risk modeling, credit strategy, and technology groups to design and build robust data pipelines - from ingestion and transformation to model deployment and monitoring.
• Develop monitoring, validation, and performance metrics to ensure accuracy, stability, and transparency in production systems.
• Identify and manage risks, dependencies, and bottlenecks to maintain delivery momentum and data reliability.

What do you need to succeed?

Must-have:

• Degree in Computer Science, Engineering, Mathematics, Statistics or a related field.
• 5+ years of experience in financial services, preferably in risk management, credit analytics, or product ownership.
• Hands‑on experience with Python, Spark, SQL, and large‑scale data management or ETL pipelines.
• Familiarity with cloud‑based data platforms (e.g., Snowflake, BigQuery) and data visualization tools.
• Strategic thinker with the ability to balance technical depth and business context.
• Familiarity with GitHub, HDFS, Hive, Parquet, and modern data stack tools.
• Proven experience working across business, data science, and engineering teams to deliver data products or analytical solutions.
• Passion for automation, continuous improvement, and scalable data solutions.
• Exceptionally strong conceptual, analytical and problem‑solving skills combined with strong written and verbal communication skills, especially in explanation of complex concepts to a non‑technical audience.

Nice‑to‑have:

• Experience building or maintaining data infrastructure and analytics frameworks within credit or financial services.
• Experience deploying models on enterprise or cloud platforms (e.g., IBM Watson, Azure, GCP).
• Understanding of credit lifecycle, lending processes, and regulatory data standards.
• Experience leading cross‑functional Agile teams or managing data‑driven projects in a matrixed enterprise environment.
• Knowledge on data access, data architecture and data storage techniques.
• Experience in automation and scheduling of data pipeline for end‑to‑end solutions.

What’s in it for you?

You’ll be part of a team shaping the future of how RBC makes credit decisions, using some of the most advanced modeling and decisioning capabilities in the industry. Your work will directly influence how millions of clients are served — and you’ll get to see your ideas go live in production.

We thrive on the challenge to be our best, thinking progressively to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits.
• Work on a dynamic topic of strategic importance.
• Ability to make a difference and lasting impact.
• Work in an agile, collaborative, progressive, and high‑performing team.

Job Skills

Business Data Analysis, Communication, Credit Analysis, Database Queries, Data Visualization, Decision Making, Long Term Planning, Operational Delivery, Quantitative Methods, Risk Management

Additional Job Details

Address: RBC WATERPARK PLACE, 88 QUEENS QUAY W: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: 2025-11-11

Application Deadline: 2025-12-15

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 believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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