Research Analyst

Solutino Pte Ltd; Hong Kong; On-site; HKD 550,000 - 800,000; Full time

Job summary

Solutino Pte Ltd is seeking a quantitatively skilled researcher to collect and clean data, perform advanced statistical analyses, and develop robust Python workflows for research and investment purposes.

The role emphasizes due diligence, macroeconomic insights, and risk monitoring, with responsibilities spanning data processing, literature review, and presenting clear recommendations to senior management.

Qualifications

• Strong foundation in statistics, including regression analysis, hypothesis testing, statistical inference, time-series analysis, correlation analysis, and interpretation of confidence intervals and statistical significance.

Responsibilities

• Collect and clean raw data for research purposes.
• Analyze data using statistical methods and tools such as Python to identify significant relationships and trends.
• Develop and refine Python scripts for statistical analysis and robustness, web scraping, and data processing.
• Interpret statistical results and translate research findings into clear, meaningful insights.
• Review academic and market literature relevant to fund research.
• Communicate research interpretations and findings effectively to internal stakeholders.
• Investment Due Diligence: Conduct thorough and efficient due diligence on potential partnerships and investment opportunities.
• Macroeconomic Analysis: Assist in developing macroeconomic theses to guide fund deployment strategies.
• Risk Monitoring: Conceptualize and establish a robust investment risk monitoring system.
• Provide ad-hoc support to the CEO and/or Head of Research as required.

Skills

Statistics

Regression analysis

Time-series analysis

Hypothesis testing

Python

Data cleaning

Web scraping

Statistical modelling

Pandas

NumPy

SciPy

Statsmodels

Matplotlib

Scikit-learn

Excel

Education

Bachelor's degree in Statistics, Econometrics, Mathematics, Data Science, Economics, Finance

Formal training in statistics and quantitative research methods

Postgraduate training in Statistics, Econometrics, Economics, Finance or related quantitative field

Tools

Pandas

NumPy

SciPy

Statsmodels

Matplotlib

Scikit-learn

Job description

1. Collect and clean raw data for research purposes.

2. Analyze data using statistical methods and tools such as Python to identify significant relationships and trends.

3. Develop and refine Python scripts for statistical analysis and robustness, web scraping, and data processing.

4. Interpret statistical results and translate research findings into clear, meaningful insights.

5. Review academic and market literature relevant to fund research.

6. Communicate research interpretations and findings effectively to internal stakeholders.

7. Investment Due Diligence: Conduct thorough and efficient due diligence on potential partnerships and investment opportunities.

8. Macroeconomic Analysis: Assist in developing macroeconomic theses to guide fund deployment strategies.

9. Risk Monitoring: Conceptualize and establish a robust investment risk monitoring system.

10. Provide ad-hoc support to the CEO and/or Head of Research as required.

Job Requirement:

Education (Requirement)

• Bachelor’s degree or above in Statistics, Econometrics, Mathematics, Data Science, Economics, Finance.
• Formal training in statistics and quantitative research methods
• Candidates with postgraduate training in Statistics, Econometrics, Economics, Finance, or a related quantitative field will be viewed favourably.

Technical & Quantitative Skills (Requirement)

• Strong foundation in statistics, including regression analysis, hypothesis testing, statistical inference, time-series analysis, correlation analysis, and interpretation of confidence intervals and statistical significance is required.
• Very Proficient in Python, particularly for:
• Data cleaning and manipulation;
• Statistical analysis and modelling;
• Web scraping and automated data collection; and
• Building repeatable research and analytical workflows.
• Familiarity with commonly used Python libraries such as Pandas, NumPy, SciPy, Statsmodels, Matplotlib and Scikit-learn.
• Ability to assess the robustness of statistical results, identify limitations in datasets and methodologies, and avoid drawing conclusions from spurious relationships.
• Strong Excel skills; familiarity with financial databases or APIs would be an advantage.

Research & Investment Skills (Preferred)

• Strong analytical and research capability, with the ability to independently review academic papers, market research, financial information and economic data.
• Ability to translate quantitative findings into clear and commercially relevant investment insights, rather than focusing solely on statistical outputs.
• Comfortable conducting structured investment and manager due diligence, including assessment of business models, financial performance, investment strategy, risks, governance and potential downside scenarios.
• An understanding of macroeconomics, financial markets and investment concepts is preferred.
• Familiarity with areas such as interest rates, inflation, economic growth, credit markets, equities, private markets and portfolio risk would be advantageous.
• Ability to conceptualize and build investment monitoring frameworks, including identification of key risk indicators, data sources, thresholds and escalation triggers.
• Comfortable working with large datasets and developing systematic approaches to monitor changes in portfolio, market and macroeconomic risks.

Personal Attributes

• Highly analytical, intellectually curious and comfortable challenging assumptions.
• Strong attention to detail and high standards of accuracy, particularly when working with data and investment-related information.
• Able to work independently and take ownership of research assignments from data collection through analysis to final recommendation or insight.
• Able to communicate complex statistical, economic and investment concepts in a clear and concise manner to senior management.
• Resourceful and willing to undertake ad-hoc research or analytical assignments

Preferred Candidate Profile:

The ideal candidate should be formally trained in statistics, highly proficient in Python, and preferably experienced in dealing with macroeconomics and financial markets.