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# Data Scientist, Risk & Quant Analytics

- **Company:** Capital Polymers, LLC
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Big Data, Data Cleansing, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Data Processing, Pandas, Scikit Learn, Information Technology, Data Management
- **Published:** September 23, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pm2u6sc6kp

## About the Role

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

## Description

* 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


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