Project Manager | Level 3

Job Title:
Project Manager | Level 3

Location:

Alpharetta GA
- Hybrid
Duration: 12 Months

Data Connectivity Lead

- Hybrid: 3 days in office per week

Key responsibilities
" Define and execute the product roadmap for AI tooling and data integration initiatives, driving products from concept to launch in a fast-paced, Agile environment.
" 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 that enable seamless access to 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 work to onboard new data sources, ensuring accuracy, consistency, and completeness of fundamental and financial data.
" Continuously assess opportunities to enhance data coverage, connectivity, and usability within AI and analytics platforms.
" Monitor and analyze product performance post-launch to drive ongoing optimization and inform future investments.
" Facilitate alignment across stakeholders, including engineering, research, analytics, and business partners, ensuring clear communication and prioritization.

Basic Qualification
" Bachelor s degree in Computer Science, Finance, or related discipline. MBA/Master s Degree desired.
" 5+ years of experience in a similar role

Required Qualifications
" Strong understanding of fundamental and financial datasets, including company financials, market data, and research data.
" Proven experience in data integration, particularly using APIs, data connectors, or ETL frameworks to enable AI or analytics use cases.
" 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 with the ability to translate complex concepts into actionable insights.
" Prior experience in financial services, investment banking, or research domains.
" Excellent organizational and stakeholder management abilities with a track record of delivering data-driven products.

Preferred Qualifications
" Deep understanding of Python, SQL, or similar scripting languages
" Knowledge of cloud data platforms (AWS, GCP, or 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.