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Executive Director, Data and AI Enablement

Pay
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Work setting
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Set the APAC Data and AI enablement roadmap and promote responsible adoption

  • Convert regional business problems into use cases, requirements and roadmaps

  • Connect APAC use cases to approved enterprise platforms and influence their roadmaps

  • Track adoption, KPI baselines and value delivery, and report to senior stakeholders

  • Build AI literacy programs, communities of practice and risk controls across APAC

From the employer’s posting
setting the enablement roadmap, aligning priorities with enterprise strategy and APAC market needs, promoting responsible adoption
converting regional and local business problems into clear use cases, requirements, solution options, roadmaps, decision criteria, and measurable outcomes
connect APAC use cases to approved enterprise platforms, influence platform roadmaps with regional needs
Ensure initiatives have clear business ownership, problem statements, benefits cases, adoption plans, KPI baselines, target outcomes, and post-implementation reviews; monitor usage and value delivery, report progress to senior stakeholders
Establish structured learning pathways, communities of practice, champion networks, playbooks, prompt libraries, hands-on labs, intake processes, prioritization criteria, decision rights, risk controls

What you’ll bring

All qualifications

Core experience

  • Bachelor’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field.
  • 10+ years of experience in data, analytics, AI enablement, digital transformation, innovation, business operations, or technology-enabled change, preferably in insurance, reinsurance, financial services, consulting, or another regulated industry.
  • 5+ years in a leadership role guiding cross-functional teams, vendors, or matrixed delivery groups through ambiguity, competing priorities, and evolving enterprise standards.
  • 5+ years of experience managing modern data infrastructure (e.g.
  • 5+ years of experience managing senior stakeholders, influencing without direct authority, and presenting complex technical or analytical topics in clear business language.
  • Knowledge of modern data platforms, analytics, AI, automation, agentic workflows, LLM-enabled solutions, and practical technology risk considerations.

Preferred experience

  • Master’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field preferred.
Qualification wording
Bachelor’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field.
10+ years of experience in data, analytics, AI enablement, digital transformation, innovation, business operations, or technology-enabled change, preferably in insurance, reinsurance, financial services, consulting, or another regulated industry.
5+ years in a leadership role guiding cross-functional teams, vendors, or matrixed delivery groups through ambiguity, competing priorities, and evolving enterprise standards.
5+ years of experience managing modern data infrastructure (e.g. Databricks, Snowflake, BigQuery etc.) and deploying scalable machine learning or LLM-powered applications.
5+ years of experience managing senior stakeholders, influencing without direct authority, and presenting complex technical or analytical topics in clear business language.
Knowledge of modern data platforms, analytics, AI, automation, agentic workflows, LLM-enabled solutions, and practical technology risk considerations.
Master’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field preferred.
Education & alternatives
Qualifications - Bachelor’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field. - Master’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field preferred.
- Bachelor’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field. - Master’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field preferred. - 10+ years of experience in data, analytics, AI enablement, digital transformation, innovation, business operations, or technology-enabled change, preferably in insurance, reinsurance, financial services, consulting, or another regulated industry.

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20262 days ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

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Where the posting names them
- 5+ years in a leadership role guiding cross-functional teams, vendors, or matrixed delivery groups through ambiguity, competing priorities, and evolving enterprise standards. - 5+ years of experience managing modern data infrastructure (e.g. Databricks, Snowflake, BigQuery etc.) and deploying scalable machine learning or LLM-powered applications. - 5+ years of experience managing senior stakeholders, influencing without direct authority, and presenting complex technical or analytical topics in clear business language.

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About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

You desire impactful work.
 

You’re RGA ready

RGA is a purpose-driven organization working to solve today’s challenges through innovation and collaboration. A Fortune 200 Company and listed among its World’s Most Admired Companies, we’re the only global reinsurance company to focus primarily on life- and health-related solutions. Join our multinational team of intelligent, motivated, and collaborative people, and help us make financial protection accessible to all.

A Brief Overview
Lead APAC Data and AI enablement by acting as the business translator between regional priorities, enterprise technology strategy, and practical market execution. Partner closely with enterprise platform, data science, technology, operations, risk, compliance, and business teams to shape safe, scalable, and reusable Data and AI capabilities that address priority business problems. Serve as a visible regional champion for Data and AI, driving adoption, responsible use, capability building, and measurable value realization across APAC markets. 

What you will do

  • Champion the APAC Data and AI enablement agenda: Act as the visible regional advocate for Data and AI, setting the enablement roadmap, aligning priorities with enterprise strategy and APAC market needs, promoting responsible adoption, and ensuring approved platforms, standards, operating models, reusable assets, and delivery practices are consistently used across the region. 
  • Translate business priorities into scalable Data and AI solutions: Serve as the business translation lead by converting regional and local business problems into clear use cases, requirements, solution options, roadmaps, decision criteria, and measurable outcomes that technology, data, and business teams can execute. 
  • Partner with enterprise platforms to scale reusable capabilities: Work closely with platform, data science, engineering, architecture, and operations teams to connect APAC use cases to approved enterprise platforms, influence platform roadmaps with regional needs, support fit-for-purpose solution design, and accelerate reuse across markets. 
  • Drive adoption, value realization, and stakeholder alignment: Ensure initiatives have clear business ownership, problem statements, benefits cases, adoption plans, KPI baselines, target outcomes, and post-implementation reviews; monitor usage and value delivery, report progress to senior stakeholders, and remove obstacles so Data and AI capabilities become embedded into business-as-usual ways of working. 
  • Build regional AI capability and responsible operating discipline: Establish structured learning pathways, communities of practice, champion networks, playbooks, prompt libraries, hands-on labs, intake processes, prioritization criteria, decision rights, risk controls, and escalation mechanisms to strengthen sustained AI literacy and responsible day-to-day use across APAC. 


Qualifications

  • Bachelor’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field.
  • Master’s Degree in Engineering, Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field preferred.
  • 10+ years of experience in data, analytics, AI enablement, digital transformation, innovation, business operations, or technology-enabled change, preferably in insurance, reinsurance, financial services, consulting, or another regulated industry.
  • 5+ years in a leadership role guiding cross-functional teams, vendors, or matrixed delivery groups through ambiguity, competing priorities, and evolving enterprise standards.
  • 5+ years of experience managing modern data infrastructure (e.g. Databricks, Snowflake, BigQuery etc.)  and deploying scalable machine learning or LLM-powered applications.
  • 5+ years of experience managing senior stakeholders, influencing without direct authority, and presenting complex technical or analytical topics in clear business language.
  • Knowledge of modern data platforms, analytics, AI, automation, agentic workflows, LLM-enabled solutions, and practical technology risk considerations. 
  • Ability to translate business problems into prioritized use cases, requirements, roadmaps, solution options, and outcome measures across the product lifecycle. 
  • Ability to lead complex projects and programs using disciplined planning, governance, risk management, dependency tracking, stakeholder alignment, and benefits realization. 
  • Understanding of responsible AI, data governance, privacy, cybersecurity, data residency, model risk, regulatory expectations, and control environments. 
  • Ability to drive adoption and change through executive communication, enablement plans, training, champion networks, feedback loops, and practical business engagement. 
  • Ability to influence senior stakeholders and work across diverse APAC markets, functions, and enterprise teams to align priorities and scale common solutions with local relevance. 
  • Native/Business-level proficiency in English.
  • Native/Business-level proficiency in Mandarin or Cantonese preferred.

#LI-JL2

What you can expect from RGA:

  • Gain valuable knowledge from and experience with diverse, caring colleagues around the world.

  • Enjoy a respectful, welcoming environment that fosters individuality and encourages pioneering thought.

  • Join the bright and creative minds of RGA, and experience vast, endless career potential.

We’re excited to get to know you and connect your unique skills with our global opportunities. To create a modern and seamless experience, we use artificial intelligence (AI) in parts of our preliminary screening process. This technology helps us personalize job recommendations, automate interview scheduling, evaluate candidates based solely on experience—without considering name, gender, or other personal details—and provide real-time answers through our chatbot. AI is used only during early screening and never makes hiring decisions. Your RGA recruiter will work closely with you every step of the way to ensure the process feels personal, thoughtful, and focused on you.

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Malaysia, Kuala Lumpur

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