Senior Data Scientist
Role Overview
Jain Global LLC seeks a Senior Data Scientist in New York, NY to collaborate with clients to assess specific analytical needs within trading activities, including cross-referencing market and alternative data, aggregating fungible assets, and researching and back-testing strategies. Requires a Master’s degree in Finance, Financial Mathematics or a related quantitative field or equivalent and three (3) years of experience applying time-series and statistical techniques, including Kalman filtering, rolling regression, and Bayesian hierarchical modeling, to forecast company KPIs and extract latent business performance signals from alternative datasets; utilizing quantamental research methods to integrate fundamental equity analysis with alternative data signals; designing and maintaining production-grade alternative data pipelines in Python and SQL, incorporating outlier detection, panel construction, data imputation using machine learning techniques and multimodal distributions, and KPI outputs; utilizing cohort analysis techniques and causal inference methods to estimate customer acquisition costs, and price elasticities in competitive consumer markets; back testing and validating alternative dataset signals using hypothesis testing, signal decay analysis, and regression-based frameworks to complement and strengthen fundamental long/short equity research; and performing DCF valuation modeling including valuation modeling with multi-scenario analysis. Telecommuting and/or working from home may be permissible pursuant to company policies.
Full Job Posting
Job Description:
Jain Global LLC seeks a Senior Data Scientist in New York, NY to collaborate with clients to assess specific analytical needs within trading activities, including cross-referencing market and alternative data, aggregating fungible assets, and researching and back-testing strategies. Requires a Master’s degree in Finance, Financial Mathematics or a related quantitative field or equivalent and three (3) years of experience applying time-series and statistical techniques, including Kalman filtering, rolling regression, and Bayesian hierarchical modeling, to forecast company KPIs and extract latent business performance signals from alternative datasets; utilizing quantamental research methods to integrate fundamental equity analysis with alternative data signals; designing and maintaining production-grade alternative data pipelines in Python and SQL, incorporating outlier detection, panel construction, data imputation using machine learning techniques and multimodal distributions, and KPI outputs; utilizing cohort analysis techniques and causal inference methods to estimate customer acquisition costs, and price elasticities in competitive consumer markets; back testing and validating alternative dataset signals using hypothesis testing, signal decay analysis, and regression-based frameworks to complement and strengthen fundamental long/short equity research; and performing DCF valuation modeling including valuation modeling with multi-scenario analysis. Telecommuting and/or working from home may be permissible pursuant to company policies. Salary Range: $250,000.00/year.
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