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Goldman Sachs


www.goldmansachs.com

Jobs

PhD – Quantitative Engineer (Dallas)

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Posted on: November 23, 2020 Apply Now
Full-Time Job Expires February 1, 2021

What We Do

At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.

Engineering, which is comprised of our Technology Division and global strategists’ groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.

Opportunities for PhDs

Risk

Risk division develops comprehensive processes to monitor, assess, and manage the risk of expected and unexpected events that may have an adverse impact on the firm. Risk teams play a critical function for the firm, driving how the firm takes and manages risk. Risk Engineering platforms and data team offers common solutions for Risk. It is at the forefront of developing world class engineering solutions, including cloud computing and big data analytics, optimized storage management, self-service toolkits, building compelling visualizations using web components, discovering information in unstructured data sources, writing automation bots and many more. The team has strong appetite to embrace latest tech stack offered in the market place to promote efficiency and agile delivery.

Consumer and Investment Management (CIMD)

The Consumer and Investment Management Division includes Goldman Sachs Asset Management (GSAM), Private Wealth Management (PWM) and our Consumer business (Marcus by Goldman Sachs). We provide asset management, wealth management and banking expertise to consumers and institutions around the world. CIMD partners with various teams across the firm to help individuals and institutions navigate changing markets and take control of their financial lives. Within the Investment Management Division, strategists (also known as ‘Strats’) play important roles in research, valuation, portfolio design and construction, surveillance and risk management analytics. A strategist will apply quantitative and analytical methods to come up with solutions that are accurate, robust and scalable.

  • GSAM Fixed Income is an investment team with a global suite of products that delivers fixed income portfolio solutions and manages assets for a broad range of clients such as pension funds, endowments, foundations, financial institutions, insurers and high net worth individuals. We focus on investing and advising clients across all sectors of the fixed income market, ranging from traditional investment grade products to more opportunistic/distressed investing.
  • Global Portfolio Solutions (GPS) is a multi-asset class investing group that sits within the Investment Management Division. It designs and develops comprehensive investment management solutions customized to meet the investment objectives and relevant constraints of clients. These solutions bring together state-of-the-art techniques for multi-asset portfolio design and implementation and reflect proprietary research and analytics conducted by the GPS team.
  • The Quantitative Investment Strategies (QIS) group, an area within GSAM which focuses on quantitative portfolio management strategies in global markets, is currently recruiting highly qualified analyst and associate candidates. QIS employs a diversified set of investment strategies to manage client assets. We are a market leader in portfolio management, global tactical asset allocation, and tax-aware strategies.

Who We Look For

Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment. We looking for highly motivated individuals who have strong quantitative skills as well as a solid background in economics, finance, mathematics, computer science, or other quantitative disciplines to join the team as a Strategist.

How You Will Fulfill Your Potential

  • Work in a dynamic, fast-paced environment that provides exposure to all areas of Risk
  • 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,
  • 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

Basic Qualifications

  • 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
Apply Now

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McNeil Building Suite 20
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