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Remote, mid-level Data Scientist at a reputable research firm with broad skillset and metro candidate pool.
Strong equity research and CFA emphasis requires finance domain expertise, limiting cross-industry transferability.
Explicit 3+ years, finance domain expectations, and required Python/SQL/ML skills create strict filters.
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Design, develop, and maintain quantitative and machine learning models to support equity research, stock screening, and investment analytics.
Collaborate with equity research analysts to translate valuation and financial analysis methodologies into scalable data-driven models and tools.
Build and manage data pipelines and workflows for model update, validation, and production deployment within CFRA's research platforms.
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Financial Engineering, Economics, or related quantitative discipline.
Minimum 3 years experience as a data scientist, quantitative analyst, or similar role, preferably within financial services, asset management, or equity research.
Strong programming skills in Python including pandas, NumPy, scikit-learn; proficiency in SQL and experience with large financial datasets.
CFA charter or active progress through CFA Program (Level II/III candidates preferred) with practical experience in equity research, valuation, or investment analysis.
Experienced in applying quantitative finance and machine learning techniques specifically for equity research and investment analytics.
Demonstrated ability to translate financial statement analysis, valuation models, and investment methodologies into data-driven solutions.
Comfortable working closely with research analysts and technical teams to productionize models and deliver validated investment signals.