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
AdvancedThinking Critically
Communication
AdvancedInteracting with Others
Developing People
AdvancedInteracting with Others
Collaboration
AdvancedInteracting with Others
Transdisciplinary Thinking
AdvancedThinking Critically
SkillsFuture Skill Levels
3 levelsBasic
Recognise and understand fundamental concepts. Apply skills in routine situations with guidance.
Intermediate
Apply skills in varied situations independently. Analyse problems and adapt approaches as needed.
Advanced
Lead and innovate in complex situations. Evaluate strategies, guide teams, and drive improvements.
Technical Skills & Competencies (TSC) Levels
6 levelsFollow
Carry out routine tasks under close supervision. Follow established procedures and guidelines.
Assist
Perform tasks with some independence. Assist in non-routine situations and apply established techniques.
Apply
Apply skills and knowledge independently in varied situations. Analyse problems and adapt approaches.
Analyse
Analyse complex situations and develop solutions. Guide and mentor junior colleagues.
Strategise
Set strategic direction and drive innovation. Evaluate trade-offs and make high-impact decisions.
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 6Business and Project Management
Inspire a culture of business and digital innovation within and beyond the organisation
Business Performance Management
Level 6General Management
Establish organisational guidelines for performance systems according to organisational mission and objectives
Learning and Development
Level 6People Development
Mentor successors, support organisational learning and develop and engage employees to develop a strong organisational base
Project Management
Level 6Business and Project Management
Direct the management and authorise ownership of multiple large, complex programmes and projects, ensuring alignment with strategic business priorities
Budgeting
Level 5Business Finance
Develop long-term financial plans and budget requirements
Business Agility
Level 5Business and Project Management
Adapt overall processes and create a working environment of business agility
Business Continuity
Level 5Business and Project Management
Develop business continuity plans, and direct resources to establish and maintain business continuity processes
Business Needs Analysis
Level 5Business and Project Management
Lead comprehensive analysis to understand underlying drivers and present a compelling business case for proposed IT solutions
Business Risk Management
Level 5Business and Project Management
Critically evaluate, review and drive organisation-wide risk mitigation and management initiatives
Change Management
Level 5Business 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 5Development and Implementation
Build spatial sensing and spatial reasoning systems
Data Design
Level 5Design 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 5Development 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 5Governance 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 5Governance 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 5Strategy 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 5Business and Project Management
Establish internal structures and processes to guide the exploration, integration and evaluation of new technologies
Intelligent Reasoning
Level 5Development and Implementation
Evaluate, design and build intelligent software systems
Manpower Planning
Level 5Business 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 5Business Development
Implementing strategies to capitalise on new business opportunities
Organisational Analysis
Level 5Strategy Planning and Implementation
Lead the conduct of functional analysis and recommending areas for enhancement in functional operations
Pattern Recognition Systems
Level 5Development and Implementation
Develop intelligent systems using machine learning techniques
People and Performance Management
Level 5People Development
Establish organisation-wide performance management strategies
Performance Management
Level 5Operations 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 5Governance and Compliance
Establish and control quality expectations in line with organisation directions and selected benchmarks
Research
Level 5Development and Implementation
Oversee and review the effective implementation of the research project within known resource constraints
Software Design
Level 5Design and Architecture
Translate complex software ideas and concepts into a design blueprint and establish key design principles and methodologies
Solution Architecture
Level 5Design and Architecture
Establish frameworks and determine relevant tools and techniques to guide the development IT solutions
Stakeholder Management
Level 5Stakeholder and Contract Management
Define a strategic stakeholder management roadmap, and lead critical discussions and negotiations, addressing escalated issues or problems encountered
Strategy Planning
Level 5Business and Project Management
Formulate the strategies and policies that are forward- looking and focuses on bottom line results
Sustainability Management
Level 5Business 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 5Development and Implementation
Implement advanced machine learning techniques in building natural language processing (NLP) models for performing common text processing tasks
Strategy Implementation
Level 4Strategy Planning and Implementation
Evaluate strategies for critical business functions to ensure plans are realistic and reflect health of business
European Skills Framework
ESCOSkills and knowledge areas required for this occupation based on European classification.
Essential
Optional
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