We are seeking a highly analytical and technically proficient Research Assistant / Technical Researcher to join our team and drive our data-centric research initiatives.

Responsibilities:

• Data Engineering & Processing: Design and implement data pipelines to extract, clean, and process large-scale financial and alternative datasets. Utilize web scraping tools and financial APIs to automate data collection workflows.

• Data Analytics & Machine Learning: Assist in developing, training, and testing machine learning models and statistical algorithms. Apply deep learning and predictive analytics to uncover market trends, financial behaviors, and risk management insights.

• Systematic Research & Prototyping: Conduct systematic technical research (including literature reviews on AI and FinTech applications). Assist in building Proof-of-Concept (PoC) models and backtesting quantitative strategies.

• Report & Visualization: Translate complex data findings into clear, actionable insights. Develop automated dashboards and robust data visualizations to support the drafting of technical reports and internal research papers.

• Collaboration & Project Support: Maintain well-documented codebases and research databases. Collaborate closely with the research team to provide technical support for ongoing FinTech projects and undertake ad-hoc analytical tasks.

Qualifications & Requirements:

• Academic Background: Bachelor’s, Master’s, or PhD degree holder with a strong academic background in Computer Science, Data Science, Artificial Intelligence, Financial Engineering, Statistics, or related highly quantitative disciplines.

• Programming Proficiency: Strong coding skills in Python (specifically libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch) and SQL. Experience with data visualization tools (e.g., Tableau, PowerBI, Matplotlib, Plotly) is essential.

• Domain Expertise: Solid expertise or strong interest in machine learning, big data analytics, and statistical modeling applied to FinTech and financial services.

• Problem-Solving & Analytical Skills: Excellent problem-solving, logical reasoning, and mathematical skills. Ability to work systematically with messy data and extract meaningful business value.

• Work Ethic & Team Fit: A self-starter with a good sense of teamwork, strong work ethic, and evidence of productivity. Capable of working independently on technical modules while contributing to overall team success.

• Experience: 1-2 years of related experience in data science, quantitative research, or technical roles is preferred. Fresh graduates with strong academic projects or relevant technical portfolios will also be highly considered.

• Language Proficiency: Good command of both written and spoken English and Chinese to facilitate technical documentation and team communication.