Data Scientist (INDIA)

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Gurugram, Haryana
In-Office
Machine Learning • Business Intelligence
The Role

Description

As a member of the Data team at Trexquant, you will be involved in parsing and analyzing large data sets, working on discovering and obtaining new sources of data, and collaborating with the Alpha and Strategy Research team to build predictive machine learning models.

Responsibilities

  • Explore and learn about a wide range of data sets that are used to develop signals for systematic quantitative strategies
  • Develop a framework to automatically download and monitor hundreds of data sources that are vital to our trading and research
  • Create data visualizations to gain insight on large data sets, such as order-by-order tick data, present findings and results
  • Research and implement machine learning techniques to identify patterns in large data sets and create new derived variables
Requirements
  • A degree in a technical discipline (computer science, mathematics, statistics, physics, etc.)
  • Experience with statistical analysis and managing of large data sets
  • Knowledge of Linux, Bash, Python, and SQL Database
  • Ability to work independently and take projects to completion, quickly learn new systems, think creatively and pay attention to details
Benefits
  • Competitive compensation, with opportunity for outstanding monetary success
  • Work in a collaborative and friendly environment, participate in decision-making process for research direction, and have opportunity to lead on new ideas

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The Company
HQ: Stamford, CT
67 Employees
Year Founded: 2012

What We Do

Being a quantitative finance firm that uses Machine Learning (ML) to create multi-asset portfolios and seek profit from the market, Trexquant has continuously improved its investment and research platform since starting operations, leveraging new and emerging technologies. Trexquant uses rigorous quantitative methods to create multi-asset portfolios in global markets. To do this, Trexquant develops trading signals using its vast and continuously growing collection of data variables used as inputs for more complex trading models called Strategies. The result is an ever-growing and adapting engine built from thousands of intricate models and tens of thousands of signals, tailor-made with the goal to outperform the market during any condition. Capital is managed across 5,500+ cash equity positions across the United States, Europe, Japan, Australia, and Canada.

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