Software Engineer

Versor Investments

New York (NY)

On-site

USD 100,000 - 140,000

Full time

14 days+

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Job summary

Versor Investments, a leading quantitative equities boutique headquartered in New York, is seeking a Software Engineer to join their trading technology team. The successful candidate will design and develop cloud-based technology stacks for investment and trading algorithms, collaborating closely with the portfolio analytics team. The role requires exceptional coding skills, preferably in Python, along with strong problem-solving abilities. A degree in Computer Science or a related field is essential, and prior financial experience is a plus. This is an excellent opportunity for individuals passionate about technology and quality software development.

Qualifications

  • Must have exceptional coding proficiency, preferably in Python/C#/ASP .Net.
  • Knowledge and experience on FIX programming to build trading systems will be advantageous.
  • At least two years of programming experience and one year of experience in data analytics.

Responsibilities

  • Design and develop highly automated cloud-based technology stack for investment and electronic trading algorithms.
  • Develop systems for trading systems and operations backend systems.
  • Create workflows and dashboards to visualize processes in real-time.

Skills

Exceptional coding proficiency in Python
Coding proficiency in C#/ASP .Net
Experience with FIX programming
Data analytics
Good oral and written communication skills

Education

B.E., B.Tech., M.Tech., or M.Sc. in Computer Science

Job description

Location

India

Role Summary

Versor Investments ("Versor") is a pioneer in applying AI and alternative data to global equity markets. As a quantitative equities boutique, we focus on systematically delivering uncorrelated alpha across single stocks, equity index futures, and corporate events. Founded in 2014 and headquartered in New York, Versor manages assets on behalf of a global client base. Our edge is defined by four core pillars that underpin how we operate and how we continue to stay at the frontier of quantitative investing. These include the use of alternative data across both developed and emerging markets, a disciplined integration of artificial intelligence with human judgment and domain expertise, deep experience in systematic investing, and an embedded approach to risk management that informs research, portfolio construction, and implementation.

The Software Engineer position will be based in Mumbai and be part of the trading technology team. He / She will collaborate with portfolio analytics team to develop system for OMS, EMS and Operations system. We are seeking candidates who have excelled in engineering specifically computer science. Prior experience in investments and finance is beneficial but not mandatory.

This role is ideal for candidates who are passionate about technology and building quality well–designed software.

Responsibilities
  • Design and develop highly automated cloud–based technology stack for investment and electronic trading algorithms.
  • Develop systems for trading systems and operations backend systems.
  • FIX onboarding for brokers and broker algorithms.
  • Create a platform to manage enormous and varied datasets.
  • Create workflows and dashboards to visualize processes in real–time.
  • Provide continuous suggestions for process improvement and performance optimization.
  • Assess different technologies and their applications.
Qualifications
  • B.E., B.Tech., M.Tech., or M.Sc. in Computer Science, Computer Engineering, Statistics or similar discipline
  • Must have exceptional coding proficiency, preferably in Python/C#/ASP .Net.
  • Knowledge and experience on FIX programming to build trading systems will be advantageous.
  • At least two years of programming experience and one year of experience in data analytics
  • Good oral and written communication skills
  • Demonstrated ability to work independently with complete ownership of projects
  • Three to five years of relevant work experience
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