Senior/Manager, Data Analytics & Translation (2-year contract)

Government Technology Agency (GovTech); Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

The Health Promotion Board (HPB) invites applications for a data analyst role within the REM division's Analytics and Translation team. You will generate data-driven insights from large longitudinal cohorts, sensors, and combined datasets to inform health-promotion strategies at a national scale.

You will build predictive models, perform segmentation, design behavioural experiments, and translate complex findings into clear narratives for internal and external stakeholders to enable

Qualifications

• Degree in statistics, data analytics, social sciences, life sciences, public health, or related quantitative discipline.
• 2–6 years of practical data analytics experience.
• Proficiency in at least one programming language (R or Python) and familiarity with Databricks/SparkR/PySpark.

Responsibilities

• Generate actionable insights through advanced analytics on diverse datasets.
• Develop predictive models and segmentation for risk stratification and programme targeting.
• Set up and support behavioural experiments and programme evaluations.
• Translate technical findings into clear, concise, and actionable narratives for stakeholders.
• Collaborate with cross-functional teams and external partners on analytics projects.

Skills

Statistics

Data analytics

Machine learning

Python

R

Databricks

SparkR

PySpark

SPSS

STATA

Communication

Project management

Education

Quantitative degree in statistics/data analytics/public health

Tools

Databricks

SparkR

PySpark

SPSS

STATA

Job description

[What the role is]The Health Promotion Board’s vision is to make Singapore a nation of healthier people.Come be a part of this journey if you’re passionate about creating boundary-pushing work that drives behavioral change.You will be part of HPB’s Research, Evaluation and Monitoring (REM) division, which drives the development of data-driven insights and analytics to inform health promotion strategies across HPB. The division focuses on translating cutting-edge research and emerging technologies into HPB programmes. By distilling learnings from diverse datasets, applied research, and innovative pilots, REM supports the translation of evidence into practice for delivery in national-scale platforms. The division also plays a key role in strengthening programme design, evaluation, and continuous improvement, ensuring that interventions are evidence-based, outcomes-driven, and relevant for real-world implementation.[What you will be working on]As a member of the Analytics and Translation team in the Research, Evaluation and Monitoring division, you will work in a cross-functional, matrix team to contribute to high-impact projects in priority growth areas.You will generate actionable insights through advanced analytics on diverse datasets (e.g. large longitudinal cohorts, sensors, and combined datasets), applying appropriate statistical and machine learning approaches to support risk prediction, population segmentation, and identification of behavioural patterns.You will support the development and application of predictive models and segmentation approaches (e.g. clustering) to inform programme targeting, intervention design, and risk stratification, ensuring outputs are robust, interpretable, and relevant for real-world decision-making.You will set up and support behavioural experiments and programme evaluations, including contributing to study design, data preparation, and analysis to distil research insights and evaluate suitability for translation into programme delivery.You will develop compelling data-driven narratives for impactful storytelling to both internal and external stakeholders, translating technical findings into clear, concise, and actionable insights that inform programme and policy decisions.You will work with cross-functional teams and external partners to support collaborations and analytics projects, contributing to delivery of strategic outcomes and facilitating knowledge sharing and learning across teams.You will support the development of data pipelines, feature engineering, and preparation of datasets to enable efficient and scalable analytics, including working with relevant data platforms where required.[What we are looking for]The ideal candidate will be a dynamic and self-motivated individual with a strong interest in advancing health promotion through data, research, and analytics. The candidate should be comfortable working at the intersection of data science and real-world application, and is motivated by translating insights into impact at scale.The candidate should also possess:Degree in statistics, data analytics, social sciences, life sciences, public health, or any related quantitative disciplineAt least 2–6 years of practical experience working with data as an analyst or in a related roleExperience in applying statistical techniques and/or machine learning methods (e.g. regression, clustering, predictive modelling) to real-world datasetsProficiency in at least one programming language (e.g. R, Python). Familiarity with Databricks, SparkR, PySpark or working with large datasets will be advantageousAdditional familiarity with statistical software (e.g. SPSS, STATA) will be a bonusFamiliarity with programme evaluation methods or quasi-experimental study designs will be advantageousStrong communication skills, especially in communicating technical findings to a non-technical audienceStrong project management skills and ability to manage multiple priorities in a fast-paced environmentComfortable working independently and as part of a teamStrong sense of intellectual curiosity and willingness to learn and seek continuous improvementAdaptable, flexible, and able to take initiative and prioritise among competing demandsSuccessful candidates will be offered a 2-year contract in the first instance.