Business Analyst, Data & AI

Cantor FitzgeraldNew York, NY

About The Position

This role sits within an AI transformation team focused on modernizing Shared Services, including Operations, Legal, Compliance, etc., through data, analytics, and emerging technologies. The Business Analyst will play a key role in identifying opportunities, translating business needs into data-driven solutions, and supporting the delivery of AI-enabled capabilities across the organization. This position requires a highly analytical, business-friendly individual who can bridge technical data concepts with practical business applications.

Requirements

  • 3-7+ years of experience as a Business Analyst, with a strong focus on data and analytics.
  • Hands-on expertise in data analysis tools like SQL, Power BI, or Python.
  • Familiarity with data governance principles and best practices.
  • Strong analytical skills and a proactive, adaptable mindset.
  • Excellent communication abilities to engage with diverse stakeholders.
  • Demonstrated hands-on experience with AI, machine learning, or advanced analytics use cases.
  • Ability to learn quickly and operate across diverse business areas.
  • A self-starter attitude with a passion for driving innovation through data and AI.

Nice To Haves

  • Experience in financial services is preferred.

Responsibilities

  • Identify and prioritize high-impact opportunities for data-driven improvements and AI use cases across Shared Services.
  • Translate business requirements into data-centric solutions, aligning with transformation goals.
  • Perform data analysis using SQL, Python, or similar tools to generate insights for AI model development.
  • Support the design and implementation of dashboards, reporting frameworks, and data models.
  • Contribute to data governance initiatives, ensuring data quality and reliability for AI solutions.
  • Collaborate with technology and product teams to deliver scalable, AI-driven solutions.
  • Communicate complex concepts and recommendations to both technical and non-technical stakeholders.
  • Participate in the design and testing of AI and machine learning solutions for operational efficiency.
  • Quickly adapt to new domains and flexibly contribute to evolving priorities across initiatives.
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