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Quantitative Engineer

2 months ago

Dallas, Texas, United States Goldman Sachs Full time
About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities and investment management firm. We are committed to fostering and advancing diversity and inclusion in our own workplace and beyond.

Job Summary

We are seeking a highly motivated PhD Quantitative Engineer to join our Risk Management team. As a Quantitative Engineer, you will work in a dynamic, fast-paced environment that provides exposure to all areas of Risk.

Responsibilities
  • Build disruptive solutions using cutting-edge technologies with measurable commercial outcomes
  • Understand business needs, facilitating and developing process workflow, data requirements, and specifications required to support implementation
  • Develop technical specifications, high-level/detailed design, testing strategies, and implementation plans from business requirements
  • Manage end-to-end systems development cycle from requirements analysis, coding, testing, UAT and maintenance
  • Build strong relationships with business-facing technology teams and business partners
  • Lead talented software engineers who are passionate about identifying patterns and building common solutions
Requirements
  • Background in a quantitative discipline (e.g. mathematics, physics, or computer science)
  • Strong problem-solving, written, verbal communication, and analytical skills
  • Familiarity with financial markets and quantitative investment approaches
  • Clear understanding of data structures, algorithms, software design, and core programming concepts
  • Programming expertise (e.g. C++, Python, R, Matlab)
  • Comfortable multi-tasking and managing multiple stakeholders
  • Strong general and technical communication skills, with an ability to effectively articulate complex financial and mathematical concepts
  • Ability to work independently and in a team environment
  • High degree of attention to detail and ability to manage complex processes, along with the judgment to balance risk/benefit tradeoffs
Preferred Qualifications
  • Prior experience in developing algorithmically complex C/C++/Java applications
  • Knowledge of modern software design for managing and exploring very large datasets
  • Experience with Machine Learning techniques such as NLP, K means clustering, Neural Networks, etc
  • Proficient at working with large and complex code bases
  • Experience with continuous delivery and deployment
  • Technologies: Web/RESTful service development: HTML 5, JavaScript/AngularJS/React/Redux, JSON, TDD (Junit), build tools (Maven/Gradle/Ant), Scala, Java, Spark, Tableau, Linux and shell scripting