Lead/ Senior Research Analyst

As a member of Team Central Provident Fund (CPF), you will play a crucial role in helping over 4 million members save for their retirement, healthcare, and housing needs as well as helping them cope with life’s uncertainties. With a fulfilling career, career growth, and development opportunities, you will be part of a big family of dedicated professionals. Join us and champion financial security for Singaporeans while leaving a lasting legacy. What you will be working on The Research and Analytics team deploys advanced data science methods to unlock the potential of data for the CPF Board. We are passionate about delivering value to internal customers, expanding our capabilities to push boundaries, and using data more pervasively in the Board. We are not confined to specific quantitative specialties and possess a variety of skillsets, from predictive analytics to econometrics and operations research. If you enjoy learning and applying diverse quantitative methods, look no further! As a Research Analyst, you will drive new applications of data science through the novel use of established methods, as well as learn and apply new data science techniques. You will collaborate with diverse teams within the Board, ranging from scheme implementers to policymakers and corporate service providers, to translate their business needs into actionable data projects. Your primary objective will be to apply your expertise to assist in making data-driven decisions and enhancing the effectiveness of their processes. Your projects and insights will be presented to the Board's senior leadership and publicised throughout the Singapore Government. Quantitative studies include, but are not confined to the following:

• Conduct predictive analytics to automate manual processes, assess the retirement landscape, and perform more targeted outreach.
• Utilise and customise large language models to streamline language-related processes such as correspondence routing and writing assistance.
• Perform simulations and econometric studies to advance policy innovations aimed at improving the retirement adequacy of CPF members.
• Analyse randomised controlled and natural experiments to enhance communication strategies with CPF members.
• Utilise cluster analysis to identify groupings of CPF members for targeted policy and outreach interventions.
• Optimise processes using methods such as operations research and reinforcement learning.

• Relevant experience in data analysis, research, or related field
• Good statistical knowledge and proficiency in applying quantitative models.
• Proficient in using quantitative methods from different disciplines will be a plus.
• Proficient in statistical software such as Python, R, and Stata.
• Ability to create engaging data visualisations, tell impactful data stories, and write in a concise yet compelling manner.
• Enjoy building relationships with people from diverse job functions to understand and pre-empt their analytical needs.
• Able to work independently to scope and drive own projects, demonstrating initiative and accountability.
• Excellent problem-solving skills with a keen attention to detail.

• A challenging and rewarding career
• A variety of formal and informal training to enhance your skills in the evolving technology landscape
• Promotion opportunities based on your capability and on-the-job performance
• A friendly work environment with like-minded colleagues to co-create and collaborate together
• A hybrid work model allowing remote work for up to 50% of the time, contingent upon the exigencies of service
• A productive yet growth-oriented workplace with a flexible dress code empowering you to decide your appropriate outfit for the day
• A comprehensive rewards package
• Annual leave and pro-family leave
• Medical and dental benefits
• Access to recreational activities
• Position is on a 1-year full-time contract directly under the payroll of CPF Board with an option to renew, contingent upon confirmation and subject to organisational needs. Additionally, there is potential for emplacement into a permanent position