AI Data Product Manager - Capital Markets

AI Data Product Manager

Required Location: Hybrid/ Hybrid/ Toronto, ON or Jersy City, NJ - 3 days a week.

Duration: 12+Months

Interview Required: Video

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1. Driver s license or State ID
2. Link to the candidates LinkedIn account.

We are seeking a highly skilled and motivated Senior Data Product Manager to join the RBC Elements team with Capital Markets Technology. This team is responsible for advancing our alternative data strategy (Alternative date is AI, Foot traffic in stores, Social Media, Logistics, Transaction monitoring, Satellite imagery or anything that gives insights to financial trends) and enabling teams across Global Research, Investment Banking, and Capital Markets to provide our clients with differentiated and nuanced data-driven perspectives. Candidates must have 10+ years of product management experience, particularly with data products in Capital Markets, Financial Services, or Technology developing data products as well as experience working as a Data Product Manager at leading financial data firms like Bloomberg or Nasdaq is highly valued/ preferred.

Job Description:

Role: Senior Product Manager Capital Markets Technology

Location: Toronto, Canada or New Jersey, USA

What is the opportunity? We are seeking a highly skilled and motivated Senior Data Product Manager to join the RBC Elements team with Capital Markets Technology. This team is responsible for advancing our alternative data strategy and enabling teams across Global Research, Investment Banking, and Capital Markets to provide our clients with differentiated and nuanced data-driven perspectives.

In this role, you will drive a portfolio of data products that deliver actionable insights and intelligence derived from diverse alternative data sets. You will bridge the gap between the business, technology, and data science, ensuring our data products meet the strategic needs of the organization while driving innovation and value creation within Capital Markets.

Key Responsibilities:

1. Product Strategy and Vision:

• Develop and execute a comprehensive product strategy and vision for alternative data products, ensuring alignment with Capital Markets goals and business objectives.
• Support execution on the alternative data strategy to deliver actionable insights for Global Research, Investment Banking, and Capital Markets teams
• Incorporate best practices such as leveraging user-centric design principles and data-driven decision-making to create innovative and scalable solutions.
• Define product OKRs and ensure alignment with organizational priorities.

1. Product Discovery and Development:

• Partner with stakeholders across functions to identify unmet needs and develop data products that address user pain points effectively.
• Conduct in-depth user research, market analysis, and competitive benchmarking to identify opportunities and guide product development.
• Collaborate with engineering, design, and data science teams to build and iterate on data products using agile methodologies.
• Define and document clear product business requirements, balancing technical feasibility with business impact.

1. End-to-End Product Lifecycle Management:

• Oversee the full lifecycle of data products, from ideation to launch, scaling, and optimization.
• Implement best-in-class product management frameworks
• Regularly evaluate product performance using KPIs and analytics, iterating based on insights to ensure continuous improvement.

1. Data Insights and Analytics:

• Collaborate with data engineering and data science teams to integrate new data sources, ensure data quality, and build advanced analytics and machine learning models
• Leverage tools and platforms like Databricks, Snowflake, and Tableau to extract insights and deliver data-driven solutions.

1. Market and Competitive Analysis:

• Stay informed about industry trends, emerging technologies, and alternative data ecosystems
• Conduct competitive analysis to ensure the product remains differentiated and aligned with market demands.

1. Governance, Compliance, and Risk Management:

• Ensure data products meet regulatory requirements and adhere to organizational policies.
• Implement robust data governance frameworks, to ensure security, compliance, and ethical use of data.

1. Stakeholder Engagement and Communication:

• Act as a trusted advisor to senior leadership, presenting product roadmaps, progress updates, and key insights.
• Build strong relationships with internal and external stakeholders, including clients, sales teams, and executive management, to ensure alignment and buy-in.

Qualifications:

• Bachelor s degree in Business, Finance, Computer Science, Data Science, or a related field (MBA or advanced degree preferred).
• 10+ years of product management experience, particularly with data products in Capital Markets, Financial Services, or Technology developing data products
• Experience working as a Data Product Manager at leading financial data firms like Bloomberg or Nasdaq is highly valued/ preferred
• Deep understanding of Capital Markets, alternative data, and financial technology ecosystems.
• Familiarity with data and AI products, as well as emerging trends in machine learning and cloud computing.
• Proficiency in data tools and platforms such as SQL, Python, Tableau, Databricks, Snowflake, and cloud platforms like Microsoft Azure, AWS, or Google Cloud.
• Familiarity with product management tools like JIRA, Confluence, Aha!, ProductBoard, and InVision.
• Proven ability to lead cross-functional teams and manage complex projects in an agile environment.
• Strong interpersonal and communication skills, with the ability to influence and align diverse stakeholders.
• Demonstrated ability to understand customer needs and translate them into impactful product features.
• Experience working with buy-side asset managers, hedge funds, or other financial institutions is a strong asset.
• Expertise in using data to make informed decisions, prioritize features, and measure product success.
• Strong ability to identify and solve complex problems, leveraging both technical and business acumen.

Preferred Skills:

• Experience with large-scale data platforms and distributed systems
• Familiarity with personalization algorithms, recommendation systems, or predictive analytics.
• Prior experience launching innovative data products in fast-paced environments.