Hiring.Camp

Quantitative Researcher Intern, PhD or Postdoc

Tower Research Capital

Location
Singapore, Hong Kong, Shanghai, Sydney · Hong Kong · Shanghai · Singapore · Sydney
Type
Internship
Department
Human Resources
Seniority
Internship
Education
PhD

Description

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. 

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities:

  • Designing, implementing, and deploying mid- to high-frequency trading algorithms 
  • Exploring trading ideas by analyzing market data and market microstructure for patterns 
  • Creating tools to analyze data for patterns 
  • Contributing to libraries of analytical computations to support market data analysis and trading
  • Developing, augmenting, and calibrating exchange simulators 

Qualifications:

  • PhD or Postdoctoral research focusing on mathematics, statistics, computer science, physics, machine learning, or related fields
  • Currently in the penultimate or final year of academic study
  • Proficient in an object-oriented programming language (C++ and Python preferred) 
  • A working knowledge of Linux/Unix 
  • Strong problem-solving abilities 
  • A passion for new technologies and ideas
  • The ability to manage multiple tasks in a fast-paced environment
  • Strong communication skills
  • Interest in financial markets

Preferred Qualifications (not required):

  • Past industry experience
  • Experience as a Teaching Assistant and/or participation in relevant Olympiads
  • Familiarity with machine learning, data analysis, market research and data modeling

Benefits:

Tower’s headquarters are in the historic Equitable Building, right in the heart of NYC’s Financial District and our impact is global, with over a dozen offices around the world. 

At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive – without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

Our benefits include:

  • Competitive compensation package
  • Free breakfast, lunch, and snacks daily
  • Exciting networking and social events
  • Opportunities to learn from senior management across the firm
  • Mentors from your alma mater and other top institutions

At Tower, you’ll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work – together.

Tower Research Capital is an equal opportunity employer.

Skills

PythonLinuxMachine LearningRisk ManagementCompliance

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