Project Manager

Compunnel, Inc.; Alpharetta (GA); On-site; USD 90,000 - 120,000; Full time

Job summary

A technology solutions provider in Alpharetta is looking for a Product Manager to define and execute the product roadmap focusing on AI tooling and data integration. This role involves collaborating with engineering and data teams to enhance access to financial datasets. Ideal candidates have a Bachelor’s in a relevant field, 3+ years of experience in a similar role, and strong analytical and communication skills. Experience in financial services is preferred.

Qualifications

• 3–5 years of experience in a similar role (2+ years acceptable if directly relevant).
• Prior experience in financial services, investment banking, or research domains.

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 data connectors.
• Partner with data engineering teams to ensure reliable data ingestion.
• Evaluate and onboard new data sources.
• Continuously assess opportunities to enhance data coverage.
• Monitor and analyze product performance post-launch.
• Facilitate alignment across stakeholders.

Skills

Understanding of fundamental and financial datasets

Data integration using APIs

Familiarity with AI/ML data pipelines

Analytical skills

Problem-solving skills

Communication skills

Organizational skills

Education

Bachelor’s degree in Computer Science, Finance, or related discipline

MBA/Master’s degree

Tools

APIs

ETL frameworks

Python

SQL

AWS

GCP

Azure

Job description

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.