Associate/Senior Associate (12 months contract), Performance Analytics (Policy)

Introduction

The Performance Analytics (Policy) team is part of the QSPA (Quantitative Strategy and Performance Analytics) team within the larger Portfolio Strategy and Risk Group which helps to provide guidance on our strategic direction and portfolio objectives.

The Performance Analytics team has 2 key responsibilities:

1. Hurdle Rate and Cost of Capital (CoC) Framework:   The team develops, refines and implements, for all our investments, Temasek’s CoC framework. The CoC framework (i) determines the minimum spread (over single hurdle) required for investment evaluation, (ii) also a key input into portfolio-level risk monitoring and (ii) the discount rates used in valuation.
2. Refinement and Calculation of Performance Metrics:   The team computes the performance of the Temasek portfolio on a bottom-up basis and is responsible for reporting Temasek’s annual “Wealth Added” (total dollar return minus dollar cost of capital), which is audited and officially published in the Temasek Review. 

The role requires strong logical and analytical capabilities in the finance domain, together with strong digital fluency and a practical understanding of technology tools and platforms. The team is actively transforming and automating its analytical, data and reporting workflows. Candidates who can identify opportunities and apply technology to improve processes, strengthen controls and increase efficiency will be highly valued.

Responsibilities

Application and Implementation of Cost of Capital Framework

• Maintain and regularly update market parameters used in the Cost of Capital (CoC) framework to support investment evaluation and monitoring.
• Support the PA team in research and analysis relating to the CoC framework, including academic research, market practices and application to new asset classes.
• Perform analytical and data-driven work to support the ongoing implementation and enhancement of the CoC framework.

Performance Measurement, Reporting and Data Management

Testing and Refinement of Performance Metrics

• Support the implementation and refinement of new performance metrics and methodologies.
• Work closely with the PA team and technology developers to perform user acceptance testing (UAT) of new metrics and enhancements to the performance calculation engine.

Performance Reporting and Data Management (Monthly Reporting and Annual Audit):

• Perform monthly reconciliation across systems to ensure position and transaction data for listed and unlisted investments are accurately captured for performance calculations.
• Generate recurring investment performance reports and support the provision of performance information to internal and external stakeholders.
• Support monthly reporting and annual performance reporting / audit processes, including preparation and validation of underlying data and calculations.
• Identify, investigate and follow up on data quality issues and reporting exceptions, working with relevant stakeholders to resolve them.

Process Automation and Workflow Improvements:

• Identify opportunities to streamline and automate recurring data, reconciliation and reporting workflows, reducing manual effort and improving process efficiency.
• Leverage technology tools and platforms to enhance performance analytics, reporting and data management processes.
• Use Python and relevant data libraries to automate data extraction, transformation, validation and reconciliation.
• Support the development of more scalable and controlled workflows, including appropriate documentation and validation of automated processes.

Requirements

• Tertiary qualification in Finance, Accounting, Business, Economics or a related discipline, with a strong foundation in financial and quantitative analysis.
• Strong logical and analytical capabilities, with the experience and ability to work with huge financial dataset, understand processes, methodologies and translate analysis into meaningful insights.
• Strong interpersonal and communication skills, with the ability to work independently and collaboratively across business and technology teams. Meticulous and detail-oriented, with a strong focus on data accuracy and quality.
• Strong digital fluency, with practical experience using Python for data extraction, transformation, analysis and/or workflow automation, and an ability to identify opportunities to improve processes through technology.
• Proficiency in Microsoft Excel and PowerPoint. Prior experience with Bloomberg, FactSet, Qlik Sense and/or UiPath would be an advantage.