CFRA Research

Independent financial research, data, and analytics.

Data Scientist - Equity Research

Data SciencePosted on Nov 10

Full-timeBengaluru, Karnataka, IndiaNo salary listedRemote

About the Job

Requirements

A Bachelor's or Master's degree in a quantitative field such as Data Science, Statistics, Computer Science, Financial Engineering, Economics, or a related discipline.
At least 3 years of experience as a data scientist, quantitative analyst, or similar role, ideally within financial services, asset management, or equity research.
A CFA charter or active progress through the CFA Program; Level II/III candidates are strongly considered, with practical experience in equity research, valuation, or investment analysis.
Strong proficiency in Python for data science, including pandas, NumPy, and scikit-learn.
A solid grounding in statistics and machine learning techniques, including regression, classification, time-series analysis, and factor/risk modeling.
Proficiency in SQL and experience working with large financial datasets from relational databases and data warehouses.
Experience with financial statement analysis, equity valuation methods (DCF, comparables, and precedent transactions), and market data sources such as Capital IQ, FactSet, or Bloomberg.
Familiarity with cloud platforms and version control.
Excellent analytical, written, and verbal communication skills, including the ability to explain complex quantitative concepts to research and business stakeholders.
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.

Responsibilities

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 research methodologies, including valuation, financial statement analysis, earnings quality, and sector-specific frameworks, 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, and communicate results to technical and non-technical stakeholders.
Build and maintain data pipelines and automated workflows for ongoing model refresh and monitoring.
Collaborate with software engineering teams to productionize models within research and analytics applications.
Perform exploratory data analysis to identify new signals, themes, or anomalies relevant to equity research.
Document methodologies, assumptions, and model limitations to institutional research standards.
Stay current on developments in quantitative finance, natural language processing for financial text, and machine learning techniques applicable to investment research.

Desired Qualifications

A CFA charter or progress through the CFA Program, particularly Level II/III candidacy, with practical equity research, valuation, or investment analysis experience.
Exposure to PyTorch or TensorFlow.
Experience applying natural language processing techniques to financial text, including earnings call transcripts, filings, or news.
Familiarity with AWS.
Prior experience at a sell-side or buy-side research firm, credit rating agency, or independent research provider.
Exposure to alternative data sources, such as satellite, web-scraped, or transaction data, for investment research.
Familiarity with backtesting frameworks and portfolio construction concepts.

CFRA is looking for a Data Scientist to join our equity research technology team in India. This role sits at the intersection of quantitative finance and data science, applying statistical modeling, machine learning, and financial domain expertise to build tools that power CFRA's independent equity research and investment analytics platforms.

The ideal candidate combines strong data science and programming skills with a genuine grounding in financial markets and equity analysis — someone who can translate raw financial data into research-grade signals, models, and insights that analysts and clients rely on. A CFA charter (or progress toward one) and hands-on equity research experience are strongly preferred, as this role requires close collaboration with research analysts and a working understanding of financial statement analysis, valuation, and investment methodology.

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

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 within financial services, asset management, or equity research
CFA charter, or active progress through the CFA Program (Level II/III candidates strongly considered), with practical experience in equity research, valuation, or investment analysis
Strong proficiency in Python for data science (pandas, NumPy, scikit-learn; exposure to PyTorch/TensorFlow a plus)
Solid grounding in statistics and machine learning techniques: regression, classification, time-series analysis, and factor/risk modeling
Proficient in SQL and working with large financial datasets from relational databases and data warehouses
Experience with financial statement analysis, equity valuation methods (DCF, comparables, precedent transactions), and market data sources (e.g., Capital IQ, FactSet, Bloomberg)
Experience with NLP techniques applied to financial text (earnings call transcripts, filings, news) is a plus
Familiarity with cloud platforms (AWS preferred) and version control (Git)
Excellent analytical, written, and verbal communication skills, with the ability to explain complex quantitative concepts to research and business stakeholders
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

Preferred Qualifications

Prior experience at a sell-side or buy-side research firm, credit rating agency, or independent research provider
Exposure to alternative data sources (satellite, web-scraped, transaction data) for investment research
Familiarity with backtesting frameworks and portfolio construction concepts

About the Company

CFRA Research

Independent financial research, data, and analytics.

CFRA Research provides independent investment research, data, and analytics through a global financial intelligence platform. It operates an ETF data platform that covers 1,600+ qualitative and 13,000+ global companies quantitatively, plus forensic accounting research to interpret public company financial reporting. Its offerings help investment professionals build portfolios and spot trading opportunities by delivering customizable, integrated insights without managing assets. Compared with rivals, CFRA remains unbiased and conflict-free because it does not run an asset management or investment banking business, and it emphasizes flexible content delivery and integration. The company aims to improve portfolio performance and reduce risk for clients by offering actionable, data-driven research and analytics that can be tailored to each client’s workflow.

Company size: 201-500
Company stage: Acquired
Total funding: Not listed
Headquarters: Charlottesville, VA
Founded: 1994

Recently Posted Jobs

Explore more opportunities at CFRA Research

See more jobs