Compunnel, Inc.
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.
KEY RESPONSIBILITIES
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. BASIC QUALIFICATIONS
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). REQUIRED QUALIFICATIONS
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. PREFERRED QUALIFICATIONS
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, GraphQL) and data integration frameworks. Demonstrated ability to partner with engineering and data science teams to operationalize AI initiatives.
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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. BASIC QUALIFICATIONS
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). REQUIRED QUALIFICATIONS
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. PREFERRED QUALIFICATIONS
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, GraphQL) and data integration frameworks. Demonstrated ability to partner with engineering and data science teams to operationalize AI initiatives.
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