Full Time Quantitative Researcher - New York, NY. Perform quant research & analysis of financial markets; formulate quant investment ideas & trading strategies.
Minimum requirements: Master's Degree in Math, Statistics, Computer Sci or related quant field + knowledge of: probability theory & statistical techniques including statistical estimation, hypothesis test development, multiple hypothesis testing, selective inference, decision analysis, supervised learning, data augmentation strategies, Monte Carlo methods & Bayesian techniques in statistical inference; linear modeling including linear regression & generalized linear models (logistic, Poisson, multinomial); data structures, algorithms, dynamic programing & complexity analysis to facilitate implementation of efficient computer programs in theory; linear algebra & real analysis including abstract vector spaces & spectral analysis (eigen-decompositions); quant data analysis & pattern recognition techniques including multivariate regression, boosting, hidden Markov models, time-series analysis, discriminative & generative models, support vector machines & neural networks, and model validation techniques including cross-validation; Python libraries for data analysis & machine learning (NumPy, SciPy, Scikit-learn, statsmodels, PyTorch, MatPlotLib, Pandas).
Must pass company's required skills assessment. Base pay: $165k-$325k/year (does not include other forms of compensation/benefits). Hybrid work attendance policy: In-office work required at below office address for collaboration days based on each team's requirement; remote work permissible for remainder of same month.
Send resume to TS-Posting@twosigma.com or mail to TS/HR Dept, Two Sigma Investments, 100 Ave of the Americas, 16 Fl, NY, NY 10013. Ref Job ID 13458.
Required skills: Test Planning & Development, Knowledge of Probability Theory, Security Clearance – TS/SCI, Financial Research, Data Analysis, Trading - Finance Investments, Multivariate Regression, Neural Network, Python, Monte Carlo Methods, Spectral Analysis.
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