Project Manager, Data Engineer, Data Science Manager

We are seeking a Product Manager to define and execute the product roadmap for AI tooling and data integration initiatives. This role will drive products from concept to launch in a fast-paced, Agile environment, collaborating with engineering, data, and AI/ML teams to enable seamless access to financial datasets.

• Define and execute the product roadmap for AI tooling and data integration initiatives.
• Translate business needs and product strategy into detailed requirements and user stories.
• Collaborate with engineering, data, and AI/ML teams to design and implement data connectors for internal and external financial datasets.
• Partner with data engineering teams to ensure reliable data ingestion, transformation, and availability for analytics and AI models.
• Evaluate and onboard new data sources, ensuring accuracy, consistency, and completeness.
• Continuously assess opportunities to enhance data coverage, connectivity, and usability within AI and analytics platforms.
• Monitor and analyze product performance post-launch to drive optimization and inform future investments.
• Facilitate alignment across stakeholders, including engineering, research, analytics, and business partners.

• Bachelor’s degree in Computer Science, Finance, or related discipline (MBA/Master’s degree desired).
• 3–5 years of experience in a similar role (2+ years acceptable if directly relevant).

• Strong understanding of fundamental and financial datasets (company financials, market data, research data).
• Proven experience in data integration using APIs, data connectors, or ETL frameworks.
• Familiarity with AI/ML data pipelines, model lifecycle, and related tooling.
• Experience working with cross-functional teams in an Agile environment.
• Strong analytical, problem-solving, and communication skills.
• Prior experience in financial services, investment banking, or research domains.
• Excellent organizational and stakeholder management abilities.

• Understanding of Python, SQL, or similar scripting languages.
• Knowledge of cloud data platforms (AWS, GCP, Azure) and modern data architectures (data lakes, warehouses, streaming).
• Familiarity with AI/ML platforms.
• Understanding of data governance, metadata management, and data security best practices in financial environments.
• Experience with API standards (REST, Graph
  
  QL) and data integration frameworks.
• Demonstrated ability to partner with engineering and data science teams to operationalize AI initiatives.