Data Scientist, Risk & Quant Analytics

Polymer Capital Hong Kong; Hong Kong; On-site; HKD 420,000 - 650,000; Full time

Job summary

Polymer Capital Hong Kong is seeking a data scientist to analyze large datasets, build and validate predictive models, and derive actionable insights for trading strategies and risk management. The role emphasizes collaboration and clear communication of complex results to non-technical stakeholders.

The ideal candidate holds an advanced degree in data science or related fields, with strong python/R skills and experience in pandas/NumPy, scikit-learn, and TensorFlow.

Qualifications

• Deep understanding of statistical methods and quantitative analysis.
• Programming in Python or R.
• Experience with pandas and NumPy.
• Familiarity with scikit-learn and TensorFlow.
• Strong written and verbal communication skills.
• Collaborative, team-oriented mindset.
• Knowledge of financial markets is a plus.
• Research or experience in behavioral finance is advantageous.

Responsibilities

• Analyze data to uncover actionable trading signals and risk insights.
• Develop predictive models and validate them rigorously.
• Collaborate with team and present findings clearly to stakeholders.
• Manage data collection, cleaning, and preprocessing for modeling.

Job description

We are seeking a skilled and motivated Data Scientist to join our team, focusing on analyzing data to uncover actionable insights and patterns. The ideal candidate will leverage statistical methods, machine learning techniques, and domain knowledge to discover signals that will drive trading strategies and enhance risk management decision-making.

Key Responsibilities

• Data Analysis & Modeling: Collect, clean, and analyze vast datasets, including market data, PM position data, social media sentiment, alternative big data, and economic indicators, to uncover trading patterns, behavior patterns, and correlations.
• Predictive Modeling: Develop and deploy machine learning, artificial intelligence, and statistical models to forecast market, industry sector, alpha, and security movements/rankings.
• Testing & Evaluation: Rigorously hypothesis testing, evaluation, and refining models to ensure robustness of decision making.
• Data Management: Handle the complex process of data preparation and management for model building and analysis.

Qualifications

Education: Advanced degree (Master’s or above) in Data Science, Statistics, Mathematics, Computer Science, or a related field.

Requirements

• Deep understanding of statistical & probability analysis and quantitative methods. Strong problem-solving abilities, with a knack for deriving insights from complex datasets.
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation libraries (e.g., pandas, NumPy)
• Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow).
• Excellent verbal and written communication skills, with the ability to effectively present complex findings clearly to diverse audiences.
• Ability to work collaboratively in a team-oriented environment and to foster a culture of learning and knowledge-sharing within the team.
• A good understanding of financial markets, market microstructure, trading algorithms and/or the business context of data science applications is a strong plus
• Research or experience related to behavioral finance is a strong plus