Data Scientist, Equity Research

This is a fully remote position, open to applicants in India.

📋 Description

• Design, construct, and maintain quantitative models and machine learning pipelines that support equity research, stock screening, and investment analytics.

• Collaborate with equity research analysts to convert valuation, financial statement analysis, earnings quality, and sector-specific methodologies into scalable data-driven models.

• Source, clean, and engineer features from both structured and unstructured financial data, which includes fundamentals, market data, earnings transcripts, and alternative datasets.

• Develop and validate predictive models, including earnings forecasts, factor models, and risk scoring.

• Effectively communicate model results to both technical and non-technical stakeholders.

• Construct and maintain data pipelines and automated workflows for model refresh and monitoring.

• Work in partnership with software engineering teams to productionize models within CFRA's research and analytics applications.

• Conduct exploratory data analysis to identify signals, themes, and anomalies pertinent to equity research.

• Document methodologies, assumptions, and model limitations to meet institutional research standards.

• Keep abreast of developments in quantitative finance, NLP for financial text, and machine learning that are relevant to investment research.

⛳️ Requirements

• Bachelor's or Master's degree in a quantitative discipline such as Data Science, Statistics, Computer Science, Financial Engineering, Economics, or a related field.

• Over 3 years of experience as a data scientist, quantitative analyst, or in a similar capacity, preferably within financial services, asset management, or equity research.

• CFA charter or active progression through the CFA Program; candidates at Level II/III will be given strong consideration.

• Practical experience in equity research, valuation, or investment analysis is essential.

• Strong expertise in Python, particularly with libraries such as pandas, NumPy, and scikit-learn; familiarity with PyTorch/TensorFlow is advantageous.

• Understanding of regression, classification, time-series analysis, and factor/risk modeling.

• Proficient in SQL with experience handling large financial datasets from relational databases and data warehouses.

• Experience with financial statement analysis, equity valuation methods including DCF, comparables, and precedent transactions, as well as market data sources like Capital IQ, FactSet, and Bloomberg.

• Experience with NLP applied to financial text is a plus.

• Familiarity with cloud platforms, preferably AWS, and version control using Git.

• Exceptional analytical, written, and verbal communication abilities.

• Strong attention to detail and a rigorous, hypothesis-driven approach to analysis.

• Capability to manage multiple projects and deadlines within 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 advantageous.

• Familiarity with backtesting frameworks and concepts of portfolio construction is preferred.

🏝️ Benefits

• 21 days of vacation.

• 8 sick days.

• 1 paid volunteer day.

• 11 - 13 holidays each year.

• Health insurance.

• Company-paid life and disability insurance.

• Competitive pay.

• Annual performance bonus.