Full-Time

Junior Commodities Fundamental Analyst

Confirmed live in the last 24 hours

Squarepoint Capital

Squarepoint Capital

501-1,000 employees

Global investment manager specializing in quantitative strategies

Quantitative Finance
Financial Services

Compensation Overview

$60kAnnually

+ Discretionary Bonuses

Entry, Junior

London, UK + 2 more

More locations: Houston, TX, USA | New York, NY, USA

Category
Sales & Trading
Finance & Banking
Required Skills
Python
Data Analysis
Requirements
  • Advanced degrees in Mathematics/Statistics/Engineering/Econometrics/Applied Economics or related subjects.
  • Experience in researching, analyzing and modelling data – ideally through prior internship experience or in a related position.
  • Coding skill in Python is required and ease with Excel is a plus.
  • Demonstrate passion for both investing and trends in commodities markets.
  • Excellent writing skills and ability to quickly synthesize thoughts and organize information.
  • Openness to tackle any project or task that is required.
  • Strong communication skills and ability to work well with colleagues across multiple teams and regions.
Responsibilities
  • Support the desks in building fundamental commodity supply and demand models.
  • Support, develop and expand analytics tools and processes for the desk.
  • Produce ad hoc analysis based on short-term market developments as request by the desk to support trade ideas.
  • Evaluate and improve market data quality.
  • Run and maintain processes related to fundamental data operations.
  • Before market opens, check that all required data and related processes are ready for the trading day.
  • During the trading day, perform ad-hoc analysis on topics linked with current trade opportunities.
  • Work on various long-term projects to build market-leading analytical models.

Squarepoint Capital specializes in managing investments using quantitative and systematic strategies. The firm builds diversified portfolios that span various asset classes and trading frequencies across global markets. By leveraging advanced technology and a comprehensive data platform, Squarepoint Capital makes informed investment decisions based on thorough research, aiming to deliver strong returns for its clients. Unlike many competitors, Squarepoint Capital focuses on systematic trading and data-driven approaches, which allows for a more structured investment process. The company's goal is to provide high-quality returns to a diverse range of institutional investors, including pension funds and sovereign wealth funds, while fostering a collaborative work environment that promotes continuous learning and professional development.

Company Stage

N/A

Total Funding

$1.1B

Headquarters

London, United Kingdom

Founded

2014

Simplify Jobs

Simplify's Take

What believers are saying

  • Squarepoint's diverse portfolio reduces risk and increases potential for high returns across various sectors.
  • The firm's commitment to quantitative research and data-driven strategies can lead to more informed and potentially profitable investment decisions.
  • Hiring experienced professionals from other hedge funds can bring fresh perspectives and innovative strategies to the firm.

What critics are saying

  • The broad investment approach may spread resources too thin, potentially impacting the depth of analysis and performance.
  • Relying heavily on quantitative research could lead to significant losses if the models fail to predict market movements accurately.

What makes Squarepoint Capital unique

  • Squarepoint Capital's strategy of acquiring stakes in a diverse range of companies, from tech to healthcare, showcases its broad investment approach.
  • The firm's focus on quantitative research and hiring talent from other hedge funds, like Romain Colas from Ovata Capital, highlights its commitment to data-driven investment strategies.
  • Squarepoint's ability to identify and invest in emerging companies, such as Cipher Mining and aTyr Pharma, sets it apart from more conservative investment firms.

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