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Data Scientist - A26265

Activate Interactive Pte Ltd
CompanyActivate Interactive Pte Ltd
CategoryUncategorised
LocationSingapore
RemoteOn-site (inferred)
EmploymentFull-time
LevelNot stated
SalaryNot stated by the employer
Posted30 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (workable)
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Description
Activate Interactive Pte Ltd (“Activate”) is a leading technology consultancy headquartered in Singapore with a presence in Malaysia and Indonesia. Our clients are empowered with quality, cost-effective, and impactful end-to-end application development, like mobile and web applications, and cloud technology that remove technology roadblocks and increase their business efficiency. We believe in positively impacting the lives of people around us and the environment we live in through the use of technology. Hence, we are committed to providing a conducive environment for all employees to realise their full potential, who in turn have the opportunity to continuously drive innovation. We are searching for our next team members to join our growing team. If you love the idea of being part of a growing company with exciting prospects in mobile and web technologies that create positive impact on people’s lives, then we would love to hear from you. Co-Development Business Unit is looking for a Data Scientist This is a fixed term contract role. The engagement is 1 year. Internal Code: A26265 What will you do? The Ministry of Digital Development and Information (MDDI) drives Singapore's digital development and is responsible for effective public communications and the Government's information and public communication policies.  Our mission is to engage hearts and minds and build a thriving digital future for all. You will join a team building and improving AI-enabled products and platforms that support effective, accessible and trusted government communications and services.   We are looking for a Data Scientist who can apply rigorous data science, natural language processing and generative AI practices to improve the quality, reliability and effectiveness of the products we build. Work with policy and communications officers, product owners, engineers, domain experts and subject-matter specialists to understand user needs and translate them into clear analytical and machine-learning problems. Develop and maintain robust evaluation frameworks and datasets for natural language, generative AI and other machine-learning use cases. Design and conduct experiments to assess and improve model quality, accuracy, consistency, reliability, latency and cost. Explore and evaluate appropriate models, techniques and emerging technologies, recommending solutions based on evidence, user needs and operational considerations. Perform systematic error analysis, identify performance gaps across use cases and user segments, and prioritise improvements with the team. Establish suitable automated and human-evaluation approaches, recognising the limitations and risks of individual metrics and AI-assisted evaluation. Partner with engineers to integrate validated improvements, define quality checks and monitor performance in production. Ensure that data, experiments and model decisions are reproducible, well documented and aligned with responsible AI, privacy and security requirements. Communicate findings, trade-offs and recommendations clearly to technical and non-technical stakeholders across MDDI and the wider public service. Requirements What are we looking for? A degree in Computer Science, Data Science, Statistics, Artificial Intelligence, Computational Linguistics or a related quantitative discipline, or equivalent practical experience. Demonstrated experience using data science or machine learning to solve real-world problems, preferably involving natural language processing, generative AI, search or information retrieval. Strong programming skills in Python and working knowledge of SQL, data processing, version control and software-development practices. Sound understanding of statistics, experimental design, evaluation methodology, sampling, error analysis and model validation. Experience working with unstructured text or other complex data types, and evaluating machine-learning or generative AI sys
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