Associate, Quantitative Analytics

About Singlife

Singlife is a leading homegrown financial services company, offering consumers a better way to financial freedom.

Through innovative, technology-enabled solutions and a wide range of products and services, Singlife provides consumers control over their financial wellbeing at every stage of their lives.

In addition to a comprehensive suite of insurance plans, employee benefits, partnerships with financial adviser channels and bancassurance, Singlife offers investment and advisory solutions through its GROW with Singlife platform.

It also offers the Singlife Account, a mobile-first insurance savings plan.

Singlife is the exclusive insurance provider for the Ministry of Defence, Ministry of Home Affairs and Public Officers Group Insurance Scheme.

Singlife is also an official signatory of the United Nations Principles for Sustainable Insurance and the United Nations-supported Principles for Responsible Investment, affirming its commitment to finding a better way to sustainability.

The merger of Aviva Singapore and Singlife was announced in September 2020 and created one of the largest homegrown financial services companies in Singapore in a deal valued at S$3.2 billion.

It was the largest insurance deal in Singapore at the time.

Singlife was subsequently acquired by Sumitomo Life in March 2024, one of Japan’s leading life insurers, which valued Singlife at S$4.6 billion, making the transaction one of the largest insurance deals in Southeast Asia.

Responsibilities

• The candidate is expected to spend the first 1-2 years building a solid information-technical foundation for the investment office, including:
• Development of the data model and internal relational database development
• Develop extreme facility with BlackRock Aladdin (risk and portfolio management system) and how this front office system interfaces with back office systems
• Automation of current reporting (e.g. risk, performance, management) using a scripting language like python
• Development of associated workflows to support the data model and automated tools
• Development and automation of tools for middle office operations (could be AI / LLM related
• Development and automation of tools for portfolio analysis (could be AI / LLM related)
• Presenting and explaining portfolio reports to internal committees
• For those candidates with less experience in finance, the expectation is the candidate will be working hard to develop a mastery in financial securities, e.g. valuation and risk.
• After the build-out phase, the candidate is expected to contribute more directly to the investment process:
• Proselytize a systematic approach to investments that is amenable / compatible with the foundational approach the candidate spent 1-2 years building and compatible with a data-driven and potentially an AI-driven approach to investment decision making.
• Research new AI-related tools for asset allocation or portfolio management
• Research and back-test quantitative trading strategies
• Specialize in and support a specific asset class
• Trade

Requirements

• As a basic pre-requisite, we require individuals with an undergraduate degree in computer science, mathematics, physics, or engineering, and with a proven ability to code (python, C/C++, Java, R, SQL) , especially in a formal software development environment.
• Some indications you are the right candidate for this role: (a) you have developed a passion or expertise in something that you were not required to do (b) you have your own github and have developed code (not part of a school project) (c) you already understand the basic mathematics of an LLM and generally like to understand how things work.
• Academic: Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering.
• Complete Fit & Proper assessments successfully on an annual basis at minimum, or when other adjunct appointments are made.
• Proven ability to code (python, C/C++, Java, R, SQL)
• Candidates with 2+ years work experience

Preferred

• Those who have developed open-source software out of their own personal interest (not part of a school project) will also be considered, as well as candidates with work experience in finance, especially fixed income securities.
• Preferences given to: Candidate with some experience in finance, especially related to fixed income and/or derivatives
• Database experience (e.g. SQL).
• Candidates familiar with BlackRock Aladdin, Citi Velocity, Bloomberg.

Key Stakeholders

External: Fron t office service provider (BlackRock) ; Reconciliation against Citi ABOR; Citi performance team.

External Fund Managers

• Others: Audit firms, Consulting firms, Asset Managers, Market Data firms
• I nternal: ALCO, BRC, Group Finance, Actuarial, Group Risk