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Polymer Capital Management in Hong Kong seeks a data science professional to collect, clean, and analyze large market datasets, build predictive models, and evaluate outcomes. You will apply statistical methods, AI techniques, and ML libraries to forecast market movements and rankings, collaborating with a team on impactful projects.
You should bring strong Python skills, experience with Pandas/NumPy/PyTorch, and a solid understanding of financial markets.
Polymer Capital Management is a market-neutral, multi-manager investment platform based in and focused on Asia. Polymer combines established institutional support and deep knowledge of local financial markets with a dedication to discovering and developing the region’s best investment talent. Polymer was established in conjunction with PAG, one of the world’s largest Asia-focused alternative asset managers, in 2019.
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.
Deep understanding of statistical & probability analysis and quantitative methods.
Hands-on experience with state-of-the-art AI techniques (e.g. model training/fine-tuning, agent workflow development), with demonstrated project delivery.
Proficiency in Python, with strong problem-solving abilities.
Experience with data manipulation and machine learning libraries (e.g., Pandas, NumPy, PyTorch, scikit-learn).
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