Associate Software Engineer C++ - MAY2019

Location: New Delhi, DL, in

Company Description

BeamStacks is a young Software Development company which is founded and being operated by IITians with overall 15 years of experience in Software Development. We work in the niche technology areas and our clients list has a number of Fortune 500 companies as well as SMBs. We believe in providing best in class work environment to our team members and we strive to setup a new benchmark in creating an employee friendly work culture.

Job Description

About the business

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Our client is engaged in trading equity markets through automated systems and mathematical models. They continuously identify trading strategies based on past patterns in market behavior and then execute these strategies over a full automated Trading system. 

What we are looking for

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An Associate Software Engineer who is excited to design new in-house algorithms. The individual should be motivated, keen to learn, display a high level of initiative and should be able to work with minimal supervision. Prior work in algorithmic trading is helpful.

Experience / Skill set Required

1. Proficiency in any Programming Language preferably C / C++

2. Problem-Solving abilities with good Quantitative & Analytical Reasoning Skills

3. Good with Data Structures (specifically with Arrays & Lists) and Algorithms

4. Excellent Debugging Skills with complex code and large data sets

5. A degree in computer science or mathematical computing or equivalent would be preferred

6. Exposure to object-oriented programming using language like C++ or any other is a plus

7. Knowledge of any other development language like Java, Python is a plus

8. Prior experience with AmiBroker's AFL progamming language is a plus

9. Working knowledge of Linux, Git, AWS is a plus

10. Strong communication skills in English or Hindi

11. Fresh Graduates with good Programming Experience in Academic Projects in College would work

Responsibilities

1. Working with large data sets to identify predictable patterns in the data

2. Identifying newer models through research / books/ internet/ networking

3. Test these patterns using historical data over the testing software

4. Test them in real market

5. Maintain and update these models in line with changing market.