Head of Data AI

CIG COMPANIES SERVICES; Orlando (FL); On-site; USD 180,000 - 260,000; Full time

Job summary

The Head of Data and AI at CIG COMPANIES SERVICES will drive the strategy, governance, and execution of data/AI initiatives across portfolio companies, turning cross-business data into measurable business value. This leader oversees enterprise data platforms, analytics, and AI/ML solutions spanning multiple industries.

They will build and lead a multidisciplinary team, define KPIs, ensure privacy/compliance, and report ROI to senior leadership, while aligning with corporate objectives and

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or related field.
• 5+ years of experience in data, analytics, or AI leadership roles with a track record of delivering high-value initiatives.
• Deep expertise with modern data platforms and tooling (e.g., cloud data warehouses, distributed processing, ML frameworks).
• Strong customer-centric mindset balanced with operational rigor.
• Proven ability to translate complex analytical outputs into business-relevant insights and actions.

Responsibilities

• Define and implement the enterprise Data & AI strategy and roadmap aligned with corporate and business-unit objectives.
• Establish data architecture and governance frameworks, including data quality, cataloging, access, privacy, and compliance.
• Oversee development and operation of data platforms (data lake/warehouse), BI dashboards, and advanced analytics models.
• Lead AI/ML initiatives such as predictive maintenance, demand forecasting, fraud detection, data and event hub, data initiatives across a wide array of SaaS providers, and personalization use cases.
• Build and manage a multidisciplinary team of data engineers, data scientists, and analytics professionals.
• Define and track KPIs and ROI for Data & AI initiatives, communicating impact to senior leadership.

Skills

Data leadership

Data architecture

Stakeholder management

ML/AI frameworks

Communication of insights

Education

Bachelor’s or Master’s degree in data-related field

Tools

Cloud data platforms

ML frameworks

Job description

The Head of Data and AI leads the strategy, governance, and execution of data and AI initiatives across portfolio companies, turning cross-business data into measurable business value. This leader oversees diverse enterprise data platforms, advanced analytics, and AI/ML solutions spanning manufacturing, airline operations, hospitality, financial services, and solar field construction.

Key Responsibilities

• Define and implement the enterprise Data & AI strategy and roadmap aligned with corporate and business-unit objectives.
• Establish data architecture and governance frameworks, including data quality, cataloging, access, privacy, and compliance.
• Oversee development and operation of data platforms (data lake/warehouse), BI dashboards, and advanced analytics models.
• Lead AI/ML initiatives such as predictive maintenance, demand forecasting, fraud detection, data and event hub, data initiatives across a wide array of SaaS providers, and personalization use cases.
• Build and manage a multidisciplinary team of data engineers, data scientists, and analytics professionals.
• Define and track KPIs and ROI for Data & AI initiatives, communicating impact to senior leadership.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or related field.
• 5+ years of experience in data, analytics, or AI leadership roles with a track record of delivering high-value initiatives.
• Deep expertise with modern data platforms and tooling (e.g., cloud data warehouses, distributed processing, ML frameworks).
• Strong customer-centric mindset balanced with operational rigor.
• Proven ability to translate complex analytical outputs into business-relevant insights and actions.

Preferred Qualifications & Skills

• Experience operating in multi-business-unit or multi-industry environments.
• Strong stakeholder management skills and ability to align diverse teams around a common data vision.
• Familiarity with responsible AI principles, data privacy regulations, and model governance practices.