Quantitative Research Associate

ANTICA ASSET MANAGEMENT PTE. LTD.; Singapore; On-site; SGD 40,000 - 70,000; Full time

Job summary

A leading company in asset management seeks a full-time Quantitative Research Associate. This role is perfect for master's graduates aiming to enhance their research skills while contributing to quantitative projects in finance and management. The candidate is expected to possess strong programming abilities, particularly in Python, along with a passion for economics and data analysis.

Benefits

Consideration for Ph.D. scholarship

Project-based employment options

Qualifications

• Previous research experience in economics, finance, or strategic management appreciated.
• Fluency in written and oral English is necessary.
• Ambition to pursue a PhD in the future is valuable.

Responsibilities

• Data cleaning using Python to prepare datasets for analysis.
• Conduct statistical tests to analyze data and identify trends.
• Scrape web data and interpret results for insights.

Skills

Data analysis

Data cleaning

Web scraping

Statistical analysis

Python

Stata

R

Communication

Education

Master’s degree in economics, Econometrics, Statistics, Finance, Business Management, or Computer Science

Tools

Python

Stata

R

Job description

Summary:

We seek a full-time pre-doctoral student/Master Graduate to work as a Quantitative Research Associate. This position is ideal for recent master’s graduates looking to develop their research skills to apply to a PhD program.

We are looking for someone who is skilled at data analysis, data cleaning, web scraping and quantitative results analysis (Please next page for specific requirement). Including using software packages such as Python, Stata and R. Python is a critical skillset. They should also have experience conducting statistical analysis on a research project analysing the correlation between social media posts and abnormal stock returns.

This is a full-time position. The company will consider offering a Ph.D. scholarship for the right candidate; terms and conditions apply. Project-based employment is welcome too.

Core Job Objectives:

• Data cleaning:Use python to preprocess raw data, including filling missing timestamps, ensuring the dataset is complete and ready for analysis.
• Data analysis:Conduct the statistical test using Python to analyze the data and identify any significant relationships or trends.
• Web scraping:Employ Python to efficiently scrape web data, specifically targeting titles and their corresponding timestamps.
• Results interpretation:Comprehend and interpret the results of the data analysis, translating complex findings into clear and meaningful insights. Communicate these interpretations effectively.
• Assist with quantitative research projects in finance, strategy, and management.
• Extract data from conventional databases (e.g., CRSP, Compustat, etc.) or hand-collect and clean data from company documents for analysis.
• Manage and clean data using software packages such as Stata, Python, and R. Proficiency in Stata is preferred.
• Conduct statistical data analysis and assisted with interpreting, writing, and disseminating findings.
• Conduct reviews of academic literature.

Requirements:

• Master’s degree in economics, Econometrics, Statistics, Finance, Business Management, or Computer Science. Prior knowledge of economics is preferred.
• Fluency in written and oral English.
• Excellent programming skills that can be applied in software packages such as Python, Stata or R. Proficiency in Python is a must.
• Previous research experience and knowledge of economics, finance, or strategic management are highly appreciated.
• Basic finance knowledge is a must.
• Excellent academic record and work ethic are required.
• Strong interest in conducting empirical research in management and economics.
• Ambition to pursue a PhD in the future or current PhD students are welcome
• Able to start work in short notice

To Apply:

• Your cover letter (max. two pages) where you explain your research experience/interest your competencies, and mention the academic area(s) you like the most, and rank them if there is more than one area (compulsory)
• A detailed CV including an email address (compulsory)
• A copy of your Official academic transcripts and detailed marks (compulsory)
• Writing sample (quantitative research preferred)