Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, insurance technology, securities, private equity, and venture capital.

Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex economic problems.

Two Sigma's data engineering platform enables us to harness some of the world's most complex & challenging content, as we structure and integrate new datasets into a diverse ecosystem of syndicated financial and industry-specific data products. Two Sigma's data scientists are focused on joining, enriching, and transforming datasets into novel creative measures of economic activity. We utilize a variety of modeling techniques to generate financially-relevant predictions feeding into Two Sigma's systematic investment management platform, we measure the performance and impact of our predictions in a variety of settings, and we further distill economic insights and thematic analyses from our data & observations.

You will take on the following responsibilities:

Design & implement granular domain-specific indicators from data, relating them to company, industry, and macroeconomic factors
Contribute to the design of investing strategies on economic predictions through multiple investing paradigms
Manage requirements for a set of dependent data products derived from a large portfolio of integrated data feeds
Contribute to data sourcing strategy across multiple industry data verticals supporting our prediction efforts
Generate a series of economic insights research reports relating trends in our indicators & predictions to investment themes

You should possess the following qualifications:

1-5+ years of experience in applied data analysis & prediction, preferably in an industry setting
Degree in a technical or quantitative disciplines, like statistics, mathematics, physics, electrical engineering, or computer science
Demonstrably strong data science modeling intuition and feature engineering creativity
Expertise in applying statistical techniques for time-series measurement/estimation and prediction
Intimate familiarity with the potential flaws & fallacies in the applications of specific statistical methods
Experience specifying & managing requirements for datasets leveraged in your analyses
Working knowledge of SQL and common data science toolkits : Python, R, Spark, Matlab
Strong written & verbal communication and presentation skills, with experience crafting a compelling narrative supported by data
A portfolio of open-data analyses or data-driven research publications would be ideal

Data Scientist - Investment Research