Sr Data Product Manager

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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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