Global Compliance - Surveillance Analytics Group - Big Data Engineer - Associate
MORE ABOUT THIS JOB
Our division prevents, detects and mitigates compliance, regulatory and reputational risk across the firm and helps to strengthen the firm's culture of compliance. Compliance accomplishes these through the firm's enterprise-wide compliance risk management program. As an independent control function and part of the firm's second line of defense, Compliance assesses the firm's compliance, regulatory and reputational risk; monitors for compliance with new or amended laws, rules and regulations; designs and implements controls, policies, procedures and training; conducts independent testing; investigates, surveils and monitors for compliance risks and breaches; and leads the firm's responses to regulatory examinations, audits and inquiries. You'll be part of a team with members from a wide range of academic and professional backgrounds, such as law, accounting, sales, and trading. We look for those who possess sound judgment, curiosity, and are able to adapt to a changing regulatory landscape.
Surveillance Analytics serve as quantitative experts working on large scale data of the firm. We are Computer Scientists, Data Modelers and Financial Engineers who design and implement risk-based surveillances models. These surveillance models detect suspicious patterns in order flows in electronic markets and low latency environments, insider trading, fraud detection and manipulation by systematic review of structured and unstructured data at large scale. The team works with Compliance Officers across all divisions of the firm, Compliance Senior Management, Business and Technology organizations.
The Surveillance Analytics Group, within the Global Compliance division, is responsible for:
- Designing and developing complex surveillances with a strong emphasis on analytical models
- Monitoring the efficiency and effectiveness of surveillance controls that have been implemented throughout the Global Compliance division
- Leading Global Compliance initiatives focused on business process re-engineering You will be working on cutting edge problems in machine learning, and distributed computing paradigms. The problems that we work on extend across big data, implementation stack to Analytics-at-scale. While not limited to, our analytical models rely heavily on:
- Bayesian inference
- Time series and behavior modeling
- Link and graph analysis
- Text mining and NLP
- Stochastic math Our compute environment is also massive, set up on a HADOOP cluster, and we frequently get into
- Building custom YARN apps
- Writing raw Mapreduce and Spark jobs
- Designing Hbase and other big data stores
- Architecting and building large scale systems
- Writing highly optimized and scalable production jobs
RESPONSIBILITIES AND QUALIFICATIONS
- The role requires an advanced degree (Masters/ PhD strongly preferred) in a computational field (Computer Science, Applied Mathematics, Engineering, or related quantitative disciplines)
- Strong in algorithms and programming (Java, C++, Python, Matlab, R etc.)
- Experience with handling large data sets & building systems
- Minimum 2 years of working experience in an analytical or a technical role
- Effective written and verbal communications skills
- Willingness to adapt in a fast-paced work environment; strong sense of urgency
- Strong work ethic
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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