Cubist Data Scientist
Confirmed live in the last 24 hours
Point72

1,001-5,000 employees

Global asset management firm investing in diverse strategies.
Company Overview
Point72 Asset Management, under the leadership of Steven Cohen, is a global investment firm that values entrepreneurial thinking and continuous adaptation, fostering a culture where ideas are welcomed from all levels within the organization. The firm's competitive advantage lies in its commitment to superior risk-adjusted returns and high ethical standards, backed by over a quarter-century of investing experience. Point72's industry leadership is evident in its strategic use of data to shape decision-making and its dedication to developing its talent, positioning it as a promising workplace for those seeking to shape the future of finance.
Quantitative Finance
Venture Capital

Company Stage

Private

Total Funding

$645.2M

Founded

2014

Headquarters

Stamford, Connecticut

Growth & Insights
Headcount

6 month growth

11%

1 year growth

31%

2 year growth

70%
Locations
London, UK
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
SQL
Java
CategoriesNew
Data & Analytics
Requirements
  • Ph.D. in computer science, mathematics, physics, statistics or another disciplines involving rigorous quantitative analysis techniques
  • At least 1 year of experience as a Data Scientist, quantitative researcher or in a similar role
  • Experience working with large data sets, including classification, regression, distribution analysis, and predictive modeling
  • Experience applying statistical tests to large data sets
  • Programming skills in SQL, TSQL, SQL Server or PL-SQL
  • Programming skills in Python and at least one of C#, C++, or Java
  • Financial industry experience preferred but not required
  • Experience dealing with intraday, tick and order book data a plus
  • Strong problem solving skills
  • Intellectual curiosity and a love of learning
  • Attention to detail and a love of process
  • Strong oral and written communication skills
Responsibilities
  • Identification of new data sets
  • Engaging with vendors to understand characteristics of datasets
  • Building processes and technology tools to ingest, tag and clean datasets
  • Analysis of datasets to generate descriptive statistics and propose potential applications of data
  • Research of potential “alpha signals” for presentation to Portfolio Managers
  • Monitoring and enhancing the automated data collection and cleansing infrastructure
  • Research on new technologies for improved data management and efficient retrieval