NTU
Manager,DataAnalytics(SeniorAnalyst,AppliedAI&DataScience)
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“Manager, Data Analytics (Senior Analyst, Applied AI & Data Science) at NTU. Skills: Data Science, Machine Learning, Applied AI, NLP. Understand operational challenges. Translate challenges into problem statements”
Industry & Context.
Translate operational challenges; Ask insightful questions; Validate assumptions with data; Navigate ambiguity
What They're Looking For.
Must Have
Bachelor's or Master's degree, 5–8 years of professional experience, 3+ years in data science/ML/AI, Python and SQL proficiency, Experience with data science libraries, Practical ML or statistical techniques, Model evaluation metrics understanding, Exploratory data analysis, Clear communication skills, Comfortable working with ambiguity
Nice to Have
Postgraduate qualifications in AI/ML, Generative AI / LLM application development, Azure AI services familiarity, Azure OpenAI familiarity, Azure AI Search familiarity, OpenAI API familiarity, NLP experience, Text analytics experience, Semantic search experience, Document intelligence use cases experience
What You'll Do.
Understand operational challenges
Translate challenges into problem statements
Define data requirements
Develop AI/ML solution approaches
Design AI and digital solutions
Own data science components
Own machine learning components
Own model evaluation components
Communicate analytical findings
Communicate model results
Communicate technical recommendations
Support management-level updates
Prepare requirements documentation
Consolidate solution design artefacts
Lead data science projects
Conduct data exploration
Perform feature analysis
Apply predictive modelling
Apply recommendation systems
Integrate AI/ML components
Conduct exploratory data analysis
Translate findings into insights
Translate findings into recommendations
Support GenAI solution development
Support GenAI solution evaluation
Prepare RAG pipelines
Work with AI agent frameworks
Work with agentic workflows
Assess AI output quality
Provide technical input on vendor proposals
Support vendor discussions
Clarify AI/data science requirements
Clarify validation criteria
Clarify acceptance test scenarios
Provide technical guidance
Share knowledge with junior team members
Stay current with AI developments
Stay current with ML developments
Identify opportunities for new approaches
How You'll Work.
Team & Collaboration
Business stakeholders; Cross-functional team; Automation and engineering specialist; Junior team members
Communication Scope
Explain technical work; Communicate findings; Communicate results; Communicate recommendations
Full Job Description
The Student and Academic Services Department (SASD) is a dedicated team committed to delivering comprehensive support across the entire student life cycle—from admission and matriculation to graduation and beyond the classroom. SASD works collaboratively with schools, colleges, and autonomous institutes to ensure a seamless and enriching academic journey for all students. This position sits with the Digital Innovations Team (DIT) which is responsible for developing AI solutions, automating administrative processes, and delivering data-driven insights that improve both staff efficiency and student experience. The successful candidate will have strong hands-on capabilities to strengthen the team's ability to deliver machine learning, NLP, forecasting, recommendation, and GenAI-enabled use cases. You will work closely with the team lead, business stakeholders, and colleagues responsible for technical implementation to translate operational challenges into practical AI and data solutions. You will be expected to bring hands-on technical depth in Python, data analysis, and machine learning, while also being able to explain your approach and findings clearly to non-technical audiences. The successful candidate would be an individual who thrive in navigating ambiguity, asking insightful questions, validating assumptions with data, and building prototypes that evolve into practical, scalable solutions. **_Key Responsibilities:_** **1\. Stakeholder Engagement & Solution Support** * Work with the team lead and business units across the university to understand operational challenges and translate them into well-defined problem statements, data requirements, and AI/ML solution approaches. * Contribute to the design of AI and digital solutions, with primary ownership of the data science, machine learning, NLP, and model evaluation components. * Communicate analytical findings, model results, and technical recommendations clearly to both technical and non-technical stakeholders,
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