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AI & Data Director - Finance & Risk Data Delivery

Job in Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listing for: Socket.dev
Full Time position
Listed on 2026-09-21
Job specializations:
  • IT/Tech
    Data Engineering, Information Security & Data Protection, Data Warehousing, Data Analyst
Salary/Wage Range or Industry Benchmark: 180000 - 300000 USD Yearly USD 180000.00 300000.00 YEAR
Job Description & How to Apply Below

If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response).

Regular or Temporary:

Regular

Language Fluency: English (Required)

Work Shift:

1st shift (United States of America)

Please review the following job description:

Manages and directs the execution of AI and data strategies, overseeing the development and deployment of AI models and architectures to enhance business processes and system performance. Leads cross-team collaboration, drives innovation and continuous improvement, enforces governance standards, manages multiple teams, and influences leadership business decisions by applying AI and analytics to solve real-world challenges.

This role is responsible for partnering closely with senior Finance, Risk, and Regulatory business leaders to define and execute the enterprise data strategy supporting critical reporting and decision-making capabilities. The position leads large-scale, complex data and transformation initiatives that enable Finance, Risk, and Regulatory Reporting functions through modern data platforms, scalable data products, and governance frameworks.

The individual will be accountable for establishing the strategic vision, architecture, and operating model for delivering trusted, high-quality data and data products that meet evolving business, regulatory, and reporting requirements. Working across business and technology organizations, this leader will drive the end-to-end delivery of data solutions, ensuring alignment with enterprise objectives, regulatory expectations, and risk management standards.

The role requires strong executive engagement, influencing senior stakeholders, setting strategic priorities, and leading cross-functional teams to deliver innovative, scalable, and compliant data capabilities that enhance reporting accuracy, operational efficiency, and business insights.

ESSENTIAL DUTIES AND RESPONSIBILITIES

1. Leads the execution of enterprise AI, data, and analytics strategies established by senior executives, ensuring alignment with business objectives, regulatory requirements, and technology roadmaps.

2. Partners directly with senior Finance, Risk, and Regulatory business leaders to define strategic priorities, influence decision-making, and deliver data-driven solutions that support critical reporting and business processes.

3. Establishes and drives the enterprise data strategy for Finance, Risk, and Regulatory Reporting, including the design, delivery, and adoption of scalable data products, data capabilities, and modern data architectures.

4. Leads large-scale, complex transformation programs and data initiatives that enhance Finance, Risk, and Regulatory Reporting capabilities while improving data quality, operational effectiveness, and business insight generation.

5. Oversees the development, deployment, and operationalization of AI models, advanced analytics solutions, and data platforms to improve business performance and enable informed decision-making.

6. Directs the design and implementation of data products and trusted data assets that support enterprise reporting, regulatory compliance, risk management, forecasting, and financial management activities.

7. Collaborates across business, technology, governance, and operations teams to integrate AI and data solutions into enterprise applications, workflows, and reporting ecosystems.

8. Establishes and enforces data governance, data quality, metadata, lineage, and control frameworks to ensure compliance with internal policies, risk standards, and regulatory expectations.

9. Evaluates and measures the effectiveness of AI, analytics, and data…

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