136 Quantitative Analysis jobs in Singapore

Your future role within QRT

• Your core objective is to create high quality predictive signals
• By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities
• Share and discuss research results, methodology, data sets and processes with other researchers
• Implement the signals and the relevant datasets within the global execution platform
• Monitor signal behaviour and model performance over time
• You would lead the full strategy research cycle from signal generation to implementation

• Min 4 years of relevant experience with strong track record
• Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering
• Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus
• Capacity to multi-task in a fast paced environment while keeping strong attention to detail
• Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#)
• Experience in exploring large datasets across multiple time frames is a plus
• Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields
• Capacity to work with autonomy within a collegial and collaborative environment
• Strong capacity to communicate with technologists, data scientists and traders across the globe
• Proven track record in delivering successful systematic strategies

ExodusPoint Capital employs a global multi-strategy investment approach to deliver compelling asymmetric returns. Our team of experienced investment professionals combines complementary liquid strategies within a robust risk framework.

This role involves collaborating with portfolio managers on research projects focused on data-driven quantitative strategies. As a Quantitative Research Specialist, you will be responsible for formulating innovative solutions for trading and risk management by working closely with technology teams.

• Collaborate with cross-functional teams to develop and implement data-driven quantitative strategies.
• Responsible for data parsing, cleaning, and processing research jobs to support portfolio managers.

• Develop and maintain complex data models and algorithms to inform investment decisions.
• Work closely with technology teams to design and implement efficient trading and risk management systems.

• Degree from a leading university in a quantitative or technical field.
• Excellent communication skills to collaborate effectively within and across teams.
• Strong knowledge of linear algebra and statistics.
• Prior experience in finance is an asset.
• Proficient in at least one programming language (e.g., Python) and relational database.

We are seeking a highly skilled Research Fellow to join our team.

The successful candidate will work closely with Dr. Doudou Zhou on a project focused on developing novel statistical and machine learning methods for analyzing complex modern data.

Key responsibilities include:

• Conducting original research in statistical inference and machine learning for high-dimensional and/or multi-source data;
• Designing and implementing algorithms for federated learning, generative modeling, and representation learning;
• Preparing manuscripts for top-tier journals and conferences in statistics, machine learning, or biomedical informatics;
• Mentoring graduate or undergraduate students when appropriate;
• Assisting with grant reporting and collaborative project coordination.

To be successful in this role, candidates should possess the following skills and qualifications:

• A Ph.D. in Statistics, Biostatistics, Computer Science, or a related quantitative discipline;
• A strong foundation in statistical theory, machine learning, or computational methods;
• Experience working with real-world biomedical or healthcare data is an advantage;
• A demonstrated record of academic publications.

This position offers a unique opportunity to contribute to cutting-edge research and collaborate with a talented team of professionals.

Benefits include:

• Opportunities for professional growth and development;
• A dynamic and inclusive work environment;
• Competitive compensation and benefits package.

Additional benefits may apply.

• Your core objective is to create high quality predictive signals
• By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities
• Share and discuss research results, methodology, data sets and processes with other researchers
• Implement the signals and the relevant datasets within the global execution platform
• Monitor signal behaviour and model performance over time
• You would lead the full strategy research cycle from signal generation to implementation

• Min 4 years of relevant experience with strong track record
• Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering
• Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus
• Capacity to multi-task in a fast paced environment while keeping strong attention to detail
• Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#)
• Experience in exploring large datasets across multiple time frames is a plus
• Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields
• Capacity to work with autonomy within a collegial and collaborative environment
• Strong capacity to communicate with technologists, data scientists and traders across the globe
• Proven track record in delivering successful systematic strategies

• Your core objective is to create high quality predictive signals
• By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities
• Share and discuss research results, methodology, data sets and processes with other researchers
• Implement the signals and the relevant datasets within the global execution platform
• Monitor signal behaviour and model performance over time
• You would lead the full strategy research cycle from signal generation to implementation

• At least 1-3 years of relevant experience
• Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering
• Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus
• Capacity to multi-task in a fast paced environment while keeping strong attention to detail
• Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#)
• Experience in exploring large datasets across multiple time frames is a plus
• Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields
• Capacity to work with autonomy within a collegial and collaborative environment
• Strong capacity to communicate with technologists, data scientists and traders across the globe
• Proven track record in delivering successful systematic strategies

Your future role within QRT
Your core objective is to create high quality predictive signals
By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities
Share and discuss research results, methodology, data sets and processes with other researchers
Implement the signals and the relevant datasets within the global execution platform
Monitor signal behaviour and model performance over time
You would lead the full strategy research cycle from signal generation to implementation
Your present skillset
Min 4 years of relevant experience with strong track record
Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering
Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus
Capacity to multi-task in a fast paced environment while keeping strong attention to detail
Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#)
Experience in exploring large datasets across multiple time frames is a plus
Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields
Capacity to work with autonomy within a collegial and collaborative environment
Strong capacity to communicate with technologists, data scientists and traders across the globe
Proven track record in delivering successful systematic strategies
#J-18808-Ljbffr

Your future role within QRT

• Your core objective is to create high quality predictive signals
• By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities
• Share and discuss research results, methodology, data sets and processes with other researchers
• Implement the signals and the relevant datasets within the global execution platform
• Monitor signal behaviour and model performance over time
• You would lead the full strategy research cycle from signal generation to implementation

Your present skillset

• Min 4 years of relevant experience with strong track record
• Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering
• Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus
• Capacity to multi-task in a fast paced environment while keeping strong attention to detail
• Coding skills required in at least one leading programing language (Python, R, Matlab and /or C++, C#)
• Experience in exploring large datasets across multiple time frames is a plus
• Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields
• Capacity to work with autonomy within a collegial and collaborative environment
• Strong capacity to communicate with technologists, data scientists and traders across the globe
• Proven track record in delivering successful systematic strategies

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WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.
WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.
Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.
The Role
This is a highly unique opportunity for a Quantitative Researcher to join a new and rapidly growing team. In this role you will partner with a close-knit team of data scientists, data engineers, technologists and data sourcing colleagues to identify and research new sector or broad Alphas based on a deep understanding of fundamentals.
Develop a structured and methodical research agenda combining fundamental knowledge, data exploration and quantitative analysis.
Become a domain expert on each fundamental topic you cover, identify key information drivers to target your research.
Conduct detailed data exploration to acquire a comprehensive understanding of the data used to generate Alphas; enrich a wide range of structured and unstructured data into datasets to enable your quantitative research.
Take a process orientated approach to understand the value drivers of your Alphas.
What You’ll Bring
At least 1 year experience as a Data Scientist, ideally in a financial / investment setting.
Proven experience of extracting insights from large and complex datasets using SQL and Python. Experience with alternative datasets a plus.
Demonstrable financial knowledge - passed at least Level I of the CFA program, or similar financial qualification (i.e., MBA or accountancy background). Thorough understanding about various valuation approaches and methods.
Expertise in time series analysis and models.
Proficient in coding in C/C++ and Python.
Excellent communications skills (both written and oral English).
Strong analytical and conceptual skills encompassing finance and related areas of financial investment.
Familiarity with various research/database platforms (Bloomberg, Reuters etc.) would be preferred.
By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction.
Copyright
2025 WorldQuant, LLC. All Rights Reserved.
WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.
Seniority level
Seniority level Entry level
Employment type
Employment type Full-time
Job function
Job function Finance and Sales
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WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.
WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.
Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.
The Role:
This is a highly unique opportunity for a Quantitative Researcher to join a new and rapidly growing team. In this role you will partner with a close-knit team of data scientists, data engineers, technologists and data sourcing colleagues to identify and research new sector or broad Alphas based on a deep understanding of fundamentals.
Develop a structured and methodical research agenda combining fundamental knowledge, data exploration and quantitative analysis.
Become a domain expert on each fundamental topic you cover, identify key information drivers to target your research.
Conduct detailed data exploration to acquire a comprehensive understanding of the data used to generate Alphas; enrich a wide range of structured and unstructured data into datasets to enable your quantitative research.
Take a process oriented approach to understand the value drivers of your Alphas.
What You’ll Bring:
At least 1 year experience as a Data Scientist, ideally in a financial / investment setting.
Proven experience of extracting insights from large and complex datasets using SQL and Python. Experience with alternative datasets a plus.
Demonstrable financial knowledge - passed at least Level I of the CFA program, or similar financial qualification (i.e., MBA or accountancy background). Thorough understanding about various valuation approaches and methods.
Expertise in time series analysis and models.
Proficient in coding in C/C++ and Python.
Excellent communications skills (both written and oral English).
Strong analytical and conceptual skills encompassing finance and related areas of financial investment.
Familiarity with various research/database platforms (Bloomberg, Reuters etc.) would be preferred.
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