Core Engineering - Data Intelligence - Research & Development Scientist
WHO WE ARE
Goldman Sachs is a leading global investment banking, securities and investment management firm that provides a wide range of services worldwide to a substantial and diversified client base that includes corporations, financial institutions, governments and high net-worth individuals.
Founded in 1869, it is one of the oldest, and largest investment banking firms. The firm is headquartered in New York and maintains offices in London, Bangalore, Frankfurt, Tokyo, Hong Kong and other major financial centers around the world.
We are committed to growing our distinctive culture and holding to our core values which always place our client's interests first. These values are reflected in our Business Principles, which emphasize integrity, commitment to excellence, innovation and teamwork.
The Goldman Sachs central machine learning (ML) team uses predictive modeling, natural language processing, anomaly detection, time series, forecasting, deep learning, and other techniques on high-volume and high-velocity data to solve problems of significant business value across multiple divisions of the firm.
RESPONSIBILITIES AND QUALIFICATIONS
ROLE AND RESPONSIBILITIES
An ML scientist in this team is responsible for deeply understanding one or more problem spaces, identifying high impact business opportunities, clearly formulating them as machine learning tasks, deftly designing and developing performant, scalable, and resilient algorithms and solutions, readily deploying the solutions, monitoring performance to ensure the desired business impact, and effectively communicating broadly at the firm. Research scientist have a PhD or equivalent in machine learning or a closely related area.
An ML engineer has similar responsibilities, with a greater emphasis on software engineering and a lesser emphasis on independent algorithm and solution design. ML engineers have a BS or MS or equivalent in machine learning or computer science or closely related area.
- Understanding of applied statistics and fundamental ML principles and techniques
- Ability to apply fundamental algorithms and data structures to efficiently solve computational problems
- Working knowledge of more than one programming language (Python, R, Java, C++ etc.)
- Ability to stay commercially focused and to always push for quantifiable commercial impact
- Strong work ethic, a sense of ownership ad urgency
- Strong analytical and problem solving skills
- Ability to collaborate effectively across global teams and communicate complex ideas in a simple manner
Goldman Sachs is a meritocracy where you will be given all the tools to advance your career. At Goldman Sachs, you will have access to excellent training programs designed to improve multiple facets of your skill portfolio. Our in-house training program, "Goldman Sachs University" offers a comprehensive series of courses that you will have access to as your career progresses. Goldman Sachs University has an impressive catalogue of courses which span technical, business and leadership skills.
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., 2018. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.
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