Artificial Intelligence Applied Researcher
The Artificial Intelligence Applied Researcher is responsible for the design and conduct of artificial intelligence (AI) research and development, synthesising insights to identify potential use cases of AI for the business. He/She presents AI research and development outcomes to senior management, business stakeholders at public forums. He determines the patentability of AI solutions and assists in the process for obtaining intellectual property rights for AI solutions. He works in a team setting 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 solutions are deployed. The AI Applied Researcher has a strong passion and curiosity for uncovering the possibilities of applying AI to address real-life business challenges and enhance organisation performance.
What Does a Artificial Intelligence Applied Researcher Do?
Key Responsibilities & Tasks
Conduct artificial intelligence (AI) research and development
- Plan and design AI research and development projects
- Manage project plans and timelines for all active and incoming AI research projects
- Evaluate AI research methodologies and processes to identify areas for improvement
- Connect with academics and institutions to collaborate and build relationships
- Review AI literature to identify emerging trends, methods, technologies and best practices
- Synthesise research to identify potential use cases and new research and development activities
- Document and present AI research and development outcomes to senior management and business stakeholders at public forums
Manage data collection and preparation
- Ensure quality and suitability of data for AI research and development
- Assess suitability of data extraction methods for research and development
- Explore new data sources and techniques to enhance research and development outcomes
- Analyse the ways in which datasets may be biased and address this in safety measures and deployment strategies
Build artificial intelligence (AI) models
- Design experiments to test AI models
- Lead the analysis, simulations and relevant testing procedures of AI models
- Synthesise insights across AI research projects to identify new research topics
- Lead prototype development of AI solutions for large scale deployment
- Provide guidance to the team on developing new AI models using suitable learning and modelling methods
- Enhance transparency of algorithms found in AI through concepts of explainability, repeatability and traceability
Manage intellectual property (IP) processes and procedures
- Perform preliminary analysis on patentability of AI solutions
- Assist in the creation, application and assignment of IP legal rights for AI solutions
- Assist in IP due diligence and landscape analysis to determine new IP for AI solutions
Do You Have the Skills for This Role?
A Artificial Intelligence Applied Researcher needs 3 core competencies. Here's what's required and at what level.
Must-Have Skills (Advanced)
Developing People
AdvancedInteracting with Others
Supporting Skills
Communication
IntermediateInteracting with Others
Learning Agility
IntermediateStaying Relevant
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 Artificial Intelligence Applied Researcher requires 17 technical skills at specific proficiency levels.
Text Analytics and Processing
Level 6Development and Implementation
Design and implement systems that can interact with users using spoken or written natural language
Business Innovation
Level 5Business and Project Management
Prioritise business innovation opportunities and design digital architectures and processes to facilitate the creation of an innovative business environment
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
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 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
Design Thinking Practice
Level 5Design and Architecture
Establish effective design thinking processes, methodologies and frameworks to proliferate design thinking across the organisation
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
Organisational Design
Level 5Design and Architecture
Design organisational structures, systems and processes
Pattern Recognition Systems
Level 5Development and Implementation
Develop intelligent systems using machine learning techniques
Project Management
Level 5Business and Project Management
Lead end-to-end management of large programmes or multiple projects concurrently, coordinating project interdependencies
Quality Standards
Level 5Governance and Compliance
Establish and control quality expectations in line with organisation directions and selected benchmarks
Computer Vision Technology
Level 4Development and Implementation
Set-up and deploy video analytics algorithms and perform system performance evaluations
Research
Level 4Development and Implementation
Design a research strategy and propose projects to meet identified research needs
Stakeholder Management
Level 4Stakeholder and Contract Management
Develop a stakeholder engagement plan and negotiate with stakeholders to arrive at mutually-beneficial arrangements
European Skills Framework
ESCOSkills and knowledge areas required for this occupation based on European classification.
Essential
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