Data Scientist

nahc.io; Hong Kong; On-site; HKD 334,800 - 446,400; Full time

Job summary

nahc.io, a fast-growing technology-driven firm in Hong Kong, is looking for a Data Scientist to join its analytics team. The role focuses on applying machine learning and statistical methods to complex financial datasets.

The ideal candidate has at least 2 years of experience, a strong foundation in quantitative analysis, and proficiency in Python with tools like Pandas and Scikit-Learn.

The position offers exposure to financial markets and real-time data systems, making it an excellent opportunity for analytics professionals.

Qualifications

• 2+ years of experience working with large-scale analytical or financial datasets.
• Strong foundation in statistics, probability, machine learning, and quantitative analysis.
• Familiarity with financial markets and trading concepts is advantageous.

Responsibilities

• Develop and deploy machine learning and statistical models for financial analytics.
• Collaborate closely with cross-functional stakeholders.
• Conduct rigorous backtesting and performance analysis.

Skills

Machine learning

Statistics

Quantitative analysis

Data querying

Critical thinking

Education

Bachelor’s or Master’s degree in a quantitative discipline

Tools

Python

SQL

Pandas

NumPy

Scikit-Learn

PyTorch

TensorFlow

Job description

A fast-growing technology-driven firm in the financial intelligence space is looking for a Data Scientist to join its high-performing analytics team. This role is ideal for someone passionate about applying machine learning, statistics, and quantitative research techniques to complex financial and alternative datasets.

You will work on developing predictive models, extracting meaningful signals from large-scale data, and supporting data-driven decision making in a highly analytical environment. The position offers strong exposure to financial markets, real-time data systems, and advanced AI/ML applications.

What you will do:

• Develop and deploy machine learning and statistical models for forecasting, pattern recognition, and financial analytics.
• Work with structured and unstructured datasets including market data, alternative datasets, and event-driven information sources.
• Design and maintain scalable data preparation and feature engineering workflows.
• Conduct rigorous backtesting, validation, and performance analysis to evaluate model robustness and reduce overfitting risk.
• Identify proprietary indicators and predictive features that improve analytical accuracy and signal quality.
• Collaborate closely with cross-functional stakeholders to translate technical findings into commercially meaningful insights.
• Continuously evaluate data integrity, model assumptions, and research methodologies to maintain high analytical standards.

What you will need:

• Bachelor’s or Master’s degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Physics, Financial Engineering, or a related field.
• 2+ years of experience working with large-scale analytical or financial datasets.
• Strong foundation in statistics, probability, machine learning, and quantitative analysis.
• Familiarity with financial markets, trading concepts, or investment data is advantageous.
• Advanced proficiency in Python, including common data science and machine learning libraries (e.g. Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow).
• Strong SQL and data querying capabilities.
• Experience handling high-volume or real-time datasets is a plus.
• Strong critical thinking skills with a detail-oriented and hypothesis-driven approach to problem solving.