Data Scientist / AI Engineer - #1761

Role Overview

The Data Scientist designs and hands-on builds the AI-enabled verification tool, combining document intelligence, computer vision and AI/ML engineering. The role works with the Business Analyst and technical delivery team to implement approved validation rules, evaluate outcomes and support production-ready MVP delivery.

Requirements & Qualifications

A. Educational Qualification & Experience
Education: A relevant qualification in Data Science, Computer Science, Artificial Intelligence, Mathematics, Statistics, Engineering or a related discipline, or equivalent practical experience
Minimum relevant experience: At least 5 years of relevant experience in data science and AI/ML solution development, including hands-on end-to-end solution design, software development, model evaluation and deployment
B. Technical & Professional Competencies
Essential (Must-Have): See Mandatory Experience below.
Preferred (Advantageous): See Preferred Experience below.

Mandatory Experience

· Ability to design and hands-on build the AI-enabled verification solution, beyond model analysis alone

· Hands-on end-to-end AI/ML solution design, software development and prototyping

· Production-quality Python

· Computer vision, OCR and document intelligence

· Multimodal and agentic AI frameworks

· Data pipelines, model evaluation and confidence calibration

· AI guardrails and safety controls

· Cloud-native deployment experience

Preferred Experience

· GCC

· GovTech PlatformAI tools, model APIs and integration with GCC-hosted applications

· SGTS toolchain

· Rules engines and spatial reasoning

· Government AI projects

· Symbol detection and legend mapping

C. Soft Skills & Communication Attributes

Strong analytical and problem-solving skills to investigate data quality issues, evaluate model outcomes and resolve implementation challenges. Good organisational skills to manage experiments, documentation and delivery priorities. Clear written and verbal communication to explain AI methods, findings and limitations to technical and non-technical stakeholders. Ability to work independently and collaborate effectively with client, the Business Analyst, Product Manager and technical delivery team.

Key Responsibilities

· Design and build the AI-enabled verification tool end-to-end

· Develop, prototype, test and integrate the solution using SFA-approved GCC-compliant tools and AI models, including suitable services available through GovTech PlatformAI, in coordination with the technical delivery team

· Implement symbol detection, text reading, legend matching and document analysis

· Implement client-approved validation rules with the Business Analyst

· Develop ground-truth datasets for pass, fail and borderline cases

· Evaluate agreement, false-pass, false-fail, routing and human-intervention rates

· Prepare AI governance and change-control artefacts

· Develop and maintain the Symbol Library required for the MVP Support performance and stress testing with the technical delivery team