Infocomm TechnologyData and AI

Head of Data Science and Artificial Intelligence

The Head of Data Science and Artificial Intelligence formulates and implement data and artificial intelligence (AI) strategies to optimise business value derived from data assets. He/She guides the AI research direction to create new algorithms and models, and reviews the feasibility of translating research and development outcomes into data and AI solutions. He oversees the development of data and AI solutions for the business to inform strategy and planning, decision-making and drive performance. He identifies potential intellectual property commercialisation opportunities for AI solutions and/or models, and oversees the preparation and application for intellectual property rights. He manages a team and is proficient in statistics, scripting and programming languages required by the organisation. He is also familiar with the relevant software platforms on which the solution is deployed on. The Head of Data Science and Artificial Intelligence is a highly effective communicator, articulating the potential value and impact of data and AI solutions on the business and influencing key business stakeholders. He is a proactive and innovative individual, possessing a strong drive to succeed amidst an evolving business environment. He develops the data and AI team's technical and leadership capabilities, and ensures compliance to the organisation's data privacy policies, ethics and governance framework, and intellectual property legislation.

What Does a Head of Data Science and Artificial Intelligence Do?

Key Responsibilities & Tasks

Implement data and artificial intelligence (AI) strategy

  • Formulate and implement strategies to identify, acquire and use appropriate data and AI models
  • Guide AI research direction based on the current and future needs of the organisation
  • Drive implementation of new data management technologies
  • Drive the organisation's AI research and development strategy and focus
  • Communicate and ensure compliance to the organisation's data privacy policies, and ethics and governance framework
  • Direct engagement initiatives to communicate the potential and value of data and AI across the organisation
  • Review research and development outcomes to ensure alignment with the organisation's vision, mission and values, and data and AI strategy
  • Establish internal policies and processes to perform regular model tuning to cater for changes in customer behaviour over time

Formulate objectives and requirements from a business perspective

  • Develop feasibility analysis plans for AI and Data Science Projects based on business requirements and expected outcomes
  • Synthesise insights from research on emerging trends, market developments and environmental scans to support feasibility analysis
  • Approve proposed AI solution for development based on an evaluation of cost-benefit, competitive and feasibility analysis
  • Communicate insights of feasibility analysis and relevant success strategies with key business stakeholders for decision making
  • Build partnerships with key service partners and customers within and across industries to accelerate the adoption of Data Science and AI initiatives

Manage intellectual property (IP) strategies, processes and procedures

  • Identify potential IP commercialisation opportunities for AI solutions and/or models
  • Liaise with external vendors on preparation and finalisation of IP applications
  • Ensure compliance to IP legislation and guidelines

Present data driven business value of data science/artificial intelligence (AI) models

  • Present data and AI model development outcomes to key stakeholders
  • Create leading-edge resources, including playbooks, guides, blog posts, videos, to advance data and AI within the organisation and for end-users
  • Present insights of data and AI model to key stakeholders
  • Articulate the potential business value and commercial impact derived from data and AI solutions

Manage people and organisation

  • Review operational strategies, policies and targets across teams and projects
  • Develop strategies for resource planning and utilisation
  • Review the utilisation of resources
  • Oversee the development of learning roadmaps for teams and functions
  • Establish performance indicators to benchmark effectiveness of learning and development programmes against best practices
  • Implement succession planning initiatives for key management positions

Do You Have the Skills for This Role?

A Head of Data Science and Artificial Intelligence needs 5 core competencies. Here's what's required and at what level.

Must-Have Skills (Advanced)

Problem Solving

Advanced

Thinking Critically

Communication

Advanced

Interacting with Others

Developing People

Advanced

Interacting with Others

Collaboration

Advanced

Interacting with Others

Transdisciplinary Thinking

Advanced

Thinking Critically

SkillsFuture Skill Levels

3 levels
1

Basic

Recognise and understand fundamental concepts. Apply skills in routine situations with guidance.

2

Intermediate

Apply skills in varied situations independently. Analyse problems and adapt approaches as needed.

3

Advanced

Lead and innovate in complex situations. Evaluate strategies, guide teams, and drive improvements.

Technical Skills & Competencies (TSC) Levels

6 levels
1

Follow

Carry out routine tasks under close supervision. Follow established procedures and guidelines.

2

Assist

Perform tasks with some independence. Assist in non-routine situations and apply established techniques.

3

Apply

Apply skills and knowledge independently in varied situations. Analyse problems and adapt approaches.

4

Analyse

Analyse complex situations and develop solutions. Guide and mentor junior colleagues.

5

Strategise

Set strategic direction and drive innovation. Evaluate trade-offs and make high-impact decisions.

6

Transform

Lead industry transformation. Establish standards, shape policy, and provide expert advisory.

Technical Skills & Competencies

A Head of Data Science and Artificial Intelligence requires 33 technical skills at specific proficiency levels.

Business Innovation

Level 6

Business and Project Management

Inspire a culture of business and digital innovation within and beyond the organisation

Business Performance Management

Level 6

General Management

Establish organisational guidelines for performance systems according to organisational mission and objectives

Learning and Development

Level 6

People Development

Mentor successors, support organisational learning and develop and engage employees to develop a strong organisational base

Project Management

Level 6

Business and Project Management

Direct the management and authorise ownership of multiple large, complex programmes and projects, ensuring alignment with strategic business priorities

Budgeting

Level 5

Business Finance

Develop long-term financial plans and budget requirements

Business Agility

Level 5

Business and Project Management

Adapt overall processes and create a working environment of business agility

Business Continuity

Level 5

Business and Project Management

Develop business continuity plans, and direct resources to establish and maintain business continuity processes

Business Needs Analysis

Level 5

Business and Project Management

Lead comprehensive analysis to understand underlying drivers and present a compelling business case for proposed IT solutions

Business Risk Management

Level 5

Business and Project Management

Critically evaluate, review and drive organisation-wide risk mitigation and management initiatives

Change Management

Level 5

Business and Project Management

Develop business readiness plan and direct business activities, processes and resources to facilitate changes and transitions, and plan change control procedures for IT initiatives

Computer Vision Technology

Level 5

Development and Implementation

Build spatial sensing and spatial reasoning systems

Data Design

Level 5

Design and Architecture

Establish a strategy for the creation of large-scale data models and structures and spearhead the implementation of database technology, architectures, software and facilities

Data Engineering

Level 5

Development and Implementation

Lead the creation of data management procedures and oversee the integration of data, ensuring optimisation of the organisation's data pipeline

Data Ethics

Level 5

Governance and Compliance

Formulate the organisation’s code of ethics, systems and processes to ensure adherence to professional, legal and ethical requirements for data usage

Data Governance

Level 5

Governance and Compliance

Develop organisation practices and standards for handling data throughout their lifecycle, resolve breaches, and oversee transfer of data between organisations

Data Strategy

Level 5

Strategy Planning and Implementation

Establish data management strategies to extract maximum value from information assets and support decision-making and business processes

Emerging Technology Synthesis

Level 5

Business and Project Management

Establish internal structures and processes to guide the exploration, integration and evaluation of new technologies

Intelligent Reasoning

Level 5

Development and Implementation

Evaluate, design and build intelligent software systems

Manpower Planning

Level 5

Business and Project Management

Formulate organisational manpower plans to bridge gaps between manpower demand and supply based on current and projected needs of the organisation

Networking

Level 5

Business Development

Implementing strategies to capitalise on new business opportunities

Organisational Analysis

Level 5

Strategy Planning and Implementation

Lead the conduct of functional analysis and recommending areas for enhancement in functional operations

Pattern Recognition Systems

Level 5

Development and Implementation

Develop intelligent systems using machine learning techniques

People and Performance Management

Level 5

People Development

Establish organisation-wide performance management strategies

Performance Management

Level 5

Operations and User Support

Evaluate and integrate new mechanisms and technology, and leverage analytics to optimise performance data, and determine implications of performance levels reported

Quality Standards

Level 5

Governance and Compliance

Establish and control quality expectations in line with organisation directions and selected benchmarks

Research

Level 5

Development and Implementation

Oversee and review the effective implementation of the research project within known resource constraints

Software Design

Level 5

Design and Architecture

Translate complex software ideas and concepts into a design blueprint and establish key design principles and methodologies

Solution Architecture

Level 5

Design and Architecture

Establish frameworks and determine relevant tools and techniques to guide the development IT solutions

Stakeholder Management

Level 5

Stakeholder and Contract Management

Define a strategic stakeholder management roadmap, and lead critical discussions and negotiations, addressing escalated issues or problems encountered

Strategy Planning

Level 5

Business and Project Management

Formulate the strategies and policies that are forward- looking and focuses on bottom line results

Sustainability Management

Level 5

Business and Project Management

Define action plans, solutions and technologies to address energy efficiency gaps, and implement sustainability practices that encourage organisational commitment

Text Analytics and Processing

Level 5

Development and Implementation

Implement advanced machine learning techniques in building natural language processing (NLP) models for performing common text processing tasks

Strategy Implementation

Level 4

Strategy Planning and Implementation

Evaluate strategies for critical business functions to ensure plans are realistic and reflect health of business

European Skills Framework

ESCO

Skills and knowledge areas required for this occupation based on European classification.

Career Paths from Head of Data Science and Artificial Intelligence

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Will AI Threaten Your Job?

57
Low riskHigh RiskHigh risk

Most at risk

provide information on study programmeswrite work-related reportsuniversity procedures

Most resilient

escort students on a field tripoversee extra-curricular activitiesliaise with educational support staff
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Quick Facts

TrackData and AI
Core Skills5
Technical Skills33
Key Tasks26

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