Data Scientist, Equity Research

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CFRA Research

51 - 200 employees

Founded 1994

💼 Consulting

⚖️ Legal

💸 Finance

💰 Private Equity Round on 2023-01

Consulting • Legal • Finance

CFRA Research is a global leader in delivering independent and unbiased investment research and financial intelligence solutions to clients worldwide. The company specializes in providing a comprehensive range of research services, including fundamental equity research, forensic accounting research, and public policy and legal research. Catering to a diverse clientele, CFRA serves wealth management firms, institutional investors, financial advisors, and self-directed individual investors by equipping them with the necessary data and analytics to navigate market cycles and make informed investment decisions. Notably, CFRA's award-winning technology and content delivery methods enable clients to integrate its insights seamlessly into their operations, ensuring flexible and cost-effective solutions across various platforms, such as web-based or API integrations. Their expertise spans consumer, energy, financials, healthcare, and technology sectors, among others, helping clients enhance portfolio performance and mitigate risks through high-quality research and data analytics.

📋 Description

• Design, build, and maintain quantitative models and machine learning pipelines supporting equity research, stock screening, and investment analytics • Partner with equity research analysts to translate valuation, financial statement analysis, earnings quality, and sector-specific methodologies into scalable data-driven models • Source, clean, and engineer features from structured and unstructured financial data, including fundamentals, market data, earnings transcripts, and alternative datasets • Develop and validate predictive models such as earnings forecasts, factor models, and risk scoring • Communicate model results to technical and non-technical stakeholders • Build and maintain data pipelines and automated workflows for model refresh and monitoring • Collaborate with software engineering teams to productionize models in CFRA's research and analytics applications • Perform exploratory data analysis to identify signals, themes, and anomalies relevant to equity research • Document methodologies, assumptions, and model limitations to institutional research standards • Stay current on quantitative finance, NLP for financial text, and machine learning developments applicable to investment research

🎯 Requirements

• Bachelor's or Master's degree in a quantitative field such as Data Science, Statistics, Computer Science, Financial Engineering, Economics, or related discipline • 3+ years of experience as a data scientist, quantitative analyst, or similar role, ideally in financial services, asset management, or equity research • CFA charter or active progress through the CFA Program; Level II/III candidates strongly considered • Practical experience in equity research, valuation, or investment analysis • Strong proficiency in Python, including pandas, NumPy, and scikit-learn; PyTorch/TensorFlow is a plus • Knowledge of regression, classification, time-series analysis, and factor/risk modeling • Proficiency in SQL and experience with large financial datasets from relational databases and data warehouses • Experience with financial statement analysis, equity valuation methods including DCF, comparables, and precedent transactions, and market data sources such as Capital IQ, FactSet, and Bloomberg • Experience with NLP applied to financial text is a plus • Familiarity with cloud platforms, preferably AWS, and Git • Excellent analytical, written, and verbal communication skills • Strong attention to detail and a rigorous, hypothesis-driven approach to analysis • Ability to manage multiple projects and deadlines in a fast-paced research environment • Prior experience at a sell-side or buy-side research firm, credit rating agency, or independent research provider is preferred • Exposure to alternative data sources for investment research is preferred • Familiarity with backtesting frameworks and portfolio construction concepts is preferred

🏖️ Benefits

• 21 days of Vacation • 8 Sick Days • 1 paid volunteer day • 11 - 13 Holidays a year • Health Insurance • Company paid Life & Disability Insurance • Competitive Pay • Annual Performance Bonus

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