Data Scientist, Risk & Quant Analytics

• 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

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