Quantitative Researcher

About Finstock, Inc.

Finstock, Inc. builds AI-powered financial research, trading analytics, quantitative research, and market intelligence tools for experienced market users, analysts, research teams, and institutions.

Our research function supports signal research, market data analysis, model diagnostics, backtesting, risk-aware decision-support workflows, and quantitative tools for financial research use cases.

About the Role

We are hiring a Quantitative Researcher to join Finstock's research team in Central, Hong Kong.

In this role, you will research, test, and evaluate quantitative signals, market patterns, statistical models, and risk-aware research workflows across financial markets. You will work closely with research, data, AI, product, and engineering teams to turn quantitative ideas into tested research outputs, model diagnostics, analytical tools, and product-ready insights.

This is a hybrid role based in Central, Hong Kong. The role requires regular in-office collaboration, with hybrid flexibility based on team needs, project requirements, and company policy.

Key Responsibilities

• Research, design, and evaluate quantitative signals, market factors, statistical indicators, and systematic research hypotheses.
• Conduct exploratory data analysis across market data, fundamentals, macroeconomic data, news-derived signals, alternative datasets, and cross-asset datasets.
• Build and maintain backtesting workflows to evaluate strategy logic, signal robustness, transaction cost assumptions, drawdowns, risk-adjusted returns, and performance stability.
• Analyze model performance using metrics such as Sharpe ratio, information ratio, hit rate, volatility, drawdown, turnover, exposure, factor sensitivity, and regime behavior.
• Develop research notebooks, model prototypes, analytical scripts, and reproducible research documentation.
• Collaborate with Data Engineers to improve market data quality, dataset structure, feature availability, and research data reliability.
• Collaborate with Software Engineers and AI Engineers to translate validated research ideas into internal tools, dashboards, APIs, model diagnostics, and product workflows.
• Support research on equities, ETFs, indices, FX, crypto assets, commodities, macro indicators, and cross-asset market relationships.
• Review financial statements, company disclosures, corporate actions, and market events where they are relevant to quantitative research questions.
• Identify data quality issues, look-ahead bias, survivorship bias, overfitting risk, data leakage, unrealistic assumptions, and fragile model behavior.
• Help build research frameworks for signal validation, factor testing, portfolio construction, scenario analysis, and risk-aware analytics.
• Prepare clear research summaries, charts, tables, technical notes, and internal presentations for research, product, and leadership teams.
• Maintain documentation for research assumptions, data sources, methodology, limitations, model behavior, and known risks.
• Follow internal security, confidentiality, data licensing, and compliance requirements when working with financial, market, vendor, or user-related data.

Required Qualifications

• 2+ years of experience in quantitative research, quantitative analysis, systematic research, trading analytics, financial data science, risk modeling, or a related role.
• Strong proficiency in Python for data analysis, statistical modeling, research prototyping, and backtesting.
• Strong understanding of statistics, probability, regression, time-series analysis, hypothesis testing, model evaluation, and quantitative finance concepts.
• Experience working with financial market data, structured datasets, APIs, time-series data, and large research datasets.
• Experience with Python libraries such as pandas, NumPy, SciPy, statsmodels, scikit-learn, matplotlib, or similar tools.
• Ability to design backtests carefully and identify common research errors such as overfitting, data leakage, survivorship bias, look-ahead bias, and unrealistic transaction assumptions.
• Strong analytical thinking and ability to distinguish statistical noise from potentially useful market structure.
• Strong written communication skills and ability to explain quantitative findings clearly to technical and non-technical stakeholders.
• Strong attention to detail, documentation discipline, and commitment to reproducible research.
• Ability to collaborate in a hybrid environment with research, data, AI, engineering, product, and analyst teams.
• Ability to work in Hong Kong in compliance with applicable laws and eligibility requirements.

Preferred Qualifications

• Master's degree or PhD in Mathematics, Statistics, Financial Engineering, Computer Science, Physics, Economics, Quantitative Finance, Operations Research, or a related quantitative discipline.
• Experience in systematic trading research, quant funds, hedge funds, prop trading, fintech, market intelligence platforms, investment research, or trading analytics.
• Familiarity with portfolio construction, factor models, risk models, optimization, regime analysis, transaction cost modeling, and signal decay analysis.
• Experience with equities, ETFs, indices, FX, crypto assets, commodities, options, futures, or multi-asset research.
• Experience with SQL, data warehouses, cloud data platforms, or research data infrastructure.
• Experience with Git, GitHub, research versioning, experiment tracking, or production research workflows.
• Experience with machine learning, NLP, alternative data, embeddings, financial document analysis, or AI-assisted research tools.
• Familiarity with Bloomberg, Refinitiv, FactSet, WRDS, exchange data, broker data, or other financial market data platforms is a plus.
• CFA, FRM, CQF, CAIA, or progress toward relevant professional credentials is a plus.
• Interest in AI-powered market intelligence, quantitative analytics, and responsible research-oriented financial technology.

What You Will Work On

You may work on projects such as:

• Quantitative signal research across equities, FX, crypto assets, commodities, indices, and macro-linked markets.
• Backtesting frameworks for signal validation and strategy diagnostics.
• Factor research, regime analysis, market anomaly detection, and risk-adjusted performance evaluation.
• Data quality checks for prices, fundamentals, corporate actions, filings, macro data, and alternative datasets.
• Research dashboards for signal monitoring, model diagnostics, portfolio exposures, and risk views.
• Internal tools that help analysts and product teams test market hypotheses more systematically.
• AI-assisted research workflows that combine market data, financial documents, and structured quantitative analysis.
• Research documentation, methodology notes, and internal presentations for product and leadership teams.

What You Will Gain

• Opportunity to contribute to quantitative research at an AI-powered financial research and market intelligence company.
• Hybrid work environment based in Central, Hong Kong.
• Direct collaboration with research, data, AI, engineering, product, finance, operations, and regional analyst teams.
• Exposure to financial market data, systematic research workflows, model diagnostics, analytics tools, and AI-assisted product development.
• A company email account and access to approved work tools, including Microsoft 365, Outlook, Teams, GitHub, market data tools, and company-approved productivity tools, subject to internal security and usage policies.
• Opportunity to participate in company offsite activities, subject to business schedule, travel eligibility, visa/documentation requirements, and company approval. Approved business-related travel, accommodation, and reasonable expenses will be covered by the company.

Important Role Boundaries

This is a quantitative research role supporting financial research workflows, model diagnostics, analytics tools, and market intelligence systems.

The role does not require or permit the employee to:

• Provide personalized investment, legal, tax, accounting, or financial advice to users or clients.
• Recommend that any individual buy, sell, or hold a security based on personal circumstances.
• Execute trades or manage client funds unless separately authorized by company policy and applicable law.
• Handle client assets, deposits, or payments.
• Promise or imply investment returns, trading profits, or risk-free outcomes.
• Present backtested or simulated results as guaranteed future performance.
• Use unauthorized data sources, violate third-party data terms, or bypass licensing restrictions.
• Bypass internal security controls, access controls, audit requirements, or approved research procedures.
• Request applicants to pay any application fee, training fee, software fee, equipment fee, or onboarding fee.

Equal Opportunity Statement

Finstock, Inc. considers qualified applicants based on role-related skills, experience, quantitative research ability, technical ability, work quality, availability, and applicable engagement requirements. We do not make hiring decisions based on age, gender, gender identity, religion, ethnicity, race, national origin, disability, sexual orientation, marital status, family status, veteran status, or any other status protected by applicable law.