About Vistra

Vistra is a leading provider of essential business services to help companies and private capital funds grow across the entire business and investment lifecycle. We work with nearly half of the Fortune Global 500, managing more than 200,000 legal entities, and working with two-thirds of the Private Equity International (PEI) 300.

Vistra is owned by BPEA EQT, the Asian private equity arm of EQT, which is the 3rd largest PE fund globally. We are currently in an exciting phase of accelerated growth and digitally powered transformation, driven by a bold vision and a dynamic executive leadership team. As we transform to become fully digital & AI powered, scale our operations and evolve our business model, we are investing in our people and culture, injecting and cultivating the skills and capabilities needed to support our future focused transformation and growth plans while ensuring we remain agile, innovative, and client focused.

Vistra operates across two primary client groups:

Vistra Funds Services (VFS) focuses on supporting Funds clients (Private Equity; Real Estate and Private Credit) through the delivery of Funds Administration; Investor Onboarding; AIFM; Depositary and similar offerings, and
Vistra Global Solutions (VGS) which is focused on Corporate (and corporate like) clients through the delivery of such offerings as Company Incorporations; Legal Entity Management & Compliance services; Financial Accounting and Tax services and Payroll and Payments services.

As Vistra continues to transform toward a platform-led, AI-enabled global delivery model, data and AI are no longer supporting functions. They are core strategic engines of margin expansion, service quality, risk management, and client experience, Data being the fundamental core of everything we do.

Role Purpose

The EVP Enterprise Data, AI & Machine Learning is accountable for defining and executing Vistra's enterprise-wide data and AI strategy, transforming how data, analytics, and AI drive operational efficiency, regulatory confidence, and build new whilst underpinning existing client value.

This role will:

Build production-grade, governed AI and a global data platform embedded into Vistra's operating model,
Enable non-linear scaling across global delivery hubs through automation and intelligence,
Ensure AI adoption is responsible, compliant, ethical, transparent and commercially impactful,
Partner tightly with Technology, Product, Operations, and Risk to embed AI into everyday workflows to industrialize the use of AI across the enterprise

This is a hands-on, execution-focused leadership role operating at global scale in a regulated environment.

Key Responsibilities

Enterprise Data, AI & ML Strategy

Define and own Vistra's global data, AI, and ML strategy, aligned to business, operating model, and risk appetite.
Define the integration, data pipeline and platform standards for Vistras global Data lakehouse
Ensure that Vistra data platform is built to be secure, AI ready, clean and well-integrated into our business processes
Build self service model for data intelligence, analytics and reporting so that the business and our customers can get what they need fast and from anywhere
Set clear priorities across analytics, automation, AI products, and platform enablement.
Ensure that legacy Data platforms are decommissioned and data is moved to our core data lakehouse
Ensure that the AI platforms are standardized and simplified to stop AI tool sprawl and run costs for the platform
Ensure that DLP is in place and no approved AI tools are in use across the enterprise
Advise ExCo and senior leaders on AI investment decisions, trade-offs, and risk exposure.

Platform, Architecture & Standards

Build and evolve a unified global data platform integrating to Vistras core systems, SaaS tools, and client-facing applications securely, is performant and where possible we can control the data quality.
Define enterprise standards for:
Data platform
AI/ML development and deployment
MLOps, model lifecycle management, and monitoring.
AI licensing and usage
AI tool adoption and review (ethical, reliable, observable, governed, secure)
Control cloud, AI and Data platform costs to ensure commercial sustainability at scale.

AI & Analytics Delivery

Lead end-to-end delivery of AI and advanced analytics initiatives across the enterprise, from use case identification to production deployment.
Build responsible, ethical, transparent policies and frameworks for AI to be delivered in an accelerated but safe manner across the enterprise
Build AI automation factory to deliver production use cases driven from our experimentation.
Partner with Product, Engineering, and Operations to embed AI into core services and client platforms.
Establish clear performance measurement and benefits-realization frameworks for AI use cases and delivery.
Be the advisory and spokesperson to the enterprise for AI delivery

Governance, Risk & Compliance

Implement strong data governance, security, and privacy controls across global operations.
Operationalize responsible AI, including bias monitoring, explainability, and model risk management.
Work closely with Risk, Compliance, Legal, and Cyber Security teams as well as the business in each country we operate in to deliver AI safely across the enterprise.

Team & Capability Building

Build and lead a global, high-performing Data & AI organization.
Establish agile delivery squads and internal capability pipelines (including university and early-career programs).
Foster a culture of accountability, experimentation, and continuous learning.

Jobs To Be Done (JTBD)

The successful candidate will be expected to deliver tangible outcomes, not just strategy.

1. Enable Scalable Global Delivery

Reduce dependence on linear headcount growth by embedding AI, automation, and analytics into accounting, payroll, governance, and compliance workflows.
Support Vistra's global delivery hubs (e.g., India, ASEAN, China) with standardized, AI-enabled platforms.
Design and deliver production ready AI into the Enterprise at scale and to meet the demands of the business
Deliver infused AI into core crown jewel assets in the company whilst building on the Data foundation technology

2. Turn Data into a Competitive Advantage

Create a unified, enterprise data foundation across fragmented core systems and SaaS platforms.
Ensure data is reliable, accessible, and decision-ready for leaders, clients, and regulators.

3. Drive Measurable Business Impact from AI

Identify and prioritize high-value use cases (e.g., productivity lift, error reduction, risk detection, client insights).
Ensure all AI and analytics initiatives deliver quantifiable ROI, not experimentation for its own sake.

4. Embed Responsible AI in a Regulated Environment

Operationalize data governance, privacy-by-design, ethical AI, and explainability across regions.
Ensure compliance with Singapore, EU, and other relevant regulatory frameworks.

5. Build a World-Class Data & AI Capability

Attract, develop, and retain elite data engineers, data scientists, ML engineers, and analytics talent.
Establish delivery squads that partner directly with business and operations teams.
Build internal capability rather than long-term dependency on external vendors.

Experience & Qualifications

Required

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
10+ years experience in data, analytics, AI, or ML roles.
5+ years in senior leadership roles managing large, cross-functional teams.
Demonstrated success delivering production-grade AI and data platforms at enterprise scale.
Strong experience with modern cloud-based data and analytics stacks (e.g. AWS, Azure, GCP).
Deep understanding of data governance, privacy, and AI risk in regulated environments.
Proven ability to translate complex technical concepts into executive and commercial outcomes.

Preferred

Experience leading data and AI transformation in regulated, multi-jurisdictional organisations (financial services, professional services, or similar).
Hands-on exposure to Generative AI, LLMs, and advanced automation use cases.
Experience operating in global delivery or shared services models.

Leadership Standards:

Enterprise Orientation – Makes decisions based on what is best for the enterprise P&L.
Judgment and Decision Authority – makes timely, high-quality decisions under ambiguity, owns consequences and does not escalate avoidable risk upwards.
Change Leadership and Transformation Delivery – Personally leads and lands major change ensuring adoption, behavior change, and realized benefits.
Influence without authority – creates alignment and movement across peers, regions and functions without relying on hierarchy or escalation.
Future-relevant capability and mindset – Possesses the skill, adaptability and mindset required for Vistra's 2025 – 2028 operating model: platformitisation, digital enablement, global simplification, and commercial discipline.

What Vistra Offers

Competitive executive compensation and performance-based incentives.
Opportunity to shape Vistra's global AI and data future.
Significant influence across strategy, operations, and client experience.
A complex, high-impact environment where AI outcomes matter.