Quantitative Research Associate

Borr Drilling; Singapore; On-site; SGD 36,000 - 60,000; Full time

Job summary

A leading company is seeking a full-time Quantitative Research Associate, ideal for recent master’s graduates aiming for a PhD. The role involves data analysis, cleaning, and web scraping using Python, contributing to research in finance and management. Successful candidates will have excellent programming skills and a strong academic background, with the potential for a Ph.D. scholarship.

Qualifications

• Master's degree in a relevant field preferred.
• Excellent programming skills in Python required.
• Strong interest in empirical research in management and economics.

Responsibilities

• Conduct data cleaning and preprocessing using Python.
• Perform statistical analysis and interpret results.
• Engage in web scraping to gather data.

Skills

Data analysis

Data cleaning

Web scraping

Statistical analysis

Fluency in English

Education

Master’s degree in Economics

Master’s degree in Econometrics

Master’s degree in Statistics

Master’s degree in Finance

Master’s degree in Business Management

Master’s degree in 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)