Securities, FICC, Franchise Analytics Strategy & Technology Strats, Quantitative Data Engineer, VP
MORE ABOUT THIS JOB
YOUR IMPACT As a front-office Strat on a quickly growing team, you will be at the forefront of a data-driven initiative to optimize decision making across multiple asset classes. You may be building a chatbot that uses Bayesian inference and Natural Language Processing to suggest potential trades, or designing metrics that analyze inquiry and trading activity to enhance client relationships. At times you will be asked to step into the high-pressure environment of the trading floor and at others you will be called upon to guide the decisions of leadership. Whether your interests fall in machine learning, business optimization or full stack development, you will find your calling amidst our diverse team. OUR IMPACT Division Description: THE SECURITIES DIVISION Our core value is building strong relationships with our institutional clients, which include corporations, financial service providers, and fund managers. We help them buy and sell financial products on exchanges around the world, raise funding, and manage risk. This is a dynamic, entrepreneurial team with a passion for the markets, with individuals who thrive in fast-paced, changing environments and are energized by a bustling trading floor. Team Description: Franchise Analytics, Strategy & Technology (FAST) FAST is a cross-divisional team in Fixed Income, Currencies & Commodities (FICC). FAST Strats partner with sales, traders and franchise managers in FICC market making businesses to understand and quantify opportunities, inefficiencies and workflow obstacles. We develop intuitive and relevant analytics to optimize business leaders' decision making and, partnering with FAST technologists, convert data-driven insights into action by embedding those analytics into simple front-line sales and trading workflow tools. HOW YOU WILL FULFILL YOUR POTENTIAL This role will draw upon your knowledge of programming and mathematics: you will be challenged to rapidly prototype early-stage solutions and build models—e.g., forecasting the trades and themes our clients may be interested in or predicting the daily trade volume of a bond. Data-driven insights from usage patterns and user feedback will drive you to condense your work into simple and efficient real-time workflow tools. You will also be required to think strategically on a higher level, proposing new business metrics or suggesting alternatives. As you gain expertise in the dynamics of the trading business, you will have the opportunity to dive deeper into your areas of interest.
RESPONSIBILITIES AND QUALIFICATIONS
BS/MS or PhD in a computational field – Applied Mathematics, Physics, Engineering, Computer Science Quantitative background including an understanding of probability and statistics Strong programming background in compiled or scripting languages (C/C++, Python, Java, etc.) Interest and desire to learn about financial markets Excellent written and verbal communication skills
Experience in data science, advanced statistics Familiarity with statistical computing languages or packages (R, numpy/scikit-learn, Matlab) Experience with distributed computing Ability to solve problems and explain the ideas that underlie them Confidence to work in a high-pressure environment and deliver results
ABOUT GOLDMAN SACHS
The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
© The Goldman Sachs Group, Inc., 2017. All rights reservedGoldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.
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