Goldman Sachs: VP/Data Scientist, Surveillance Analytics Group

Lead the creation and development of big data analytics function to identify potential risk behaviors, including market manipulation, insider trading, and money laundering.

The Goldman Sachs Group Company: The Goldman Sachs Group
Location: Jersey City, NJ

Job Summary & Responsibilities
The Goldman Sachs Group, Inc. is a leading global financial services firm providing investment banking, securities and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments and high-net-worth individuals. The firm is headquartered in New York and maintains offices in London, Frankfurt, Tokyo, Hong Kong and other major financial centers around the world.

Department Summary

The Surveillance Analytics Group, within the Global Compliance division, is responsible for:
  • Working with both Compliance Officers and the Technology Organization to define, prioritize, and address surveillance-related needs. Areas of focus include trade/transaction surveillances (e.g., market manipulation, insider trading), anti-money laundering surveillances, and e-communications reviews
  • Designing and developing complex, profile-based, surveillances with a strong emphasis on analytical models
  • Establishing a function to lead data-driven investigations through forensic reporting and big data techniques
  • 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

The group also works with Compliance Senior Management, Compliance Officers, Business and Technology organizations in order to develop quantitative models that address key compliance risks. Examples of some of the key techniques employed include:
  • Risk scoring systems
  • Text analytics
  • Link analysis for relationship modeling
  • Behavior modeling

Summary of the Role

The Global Compliance division's surveillance program leverages multi-disciplinary data in its surveillance program. As a next stage of evolution, we are seeking to establish a big data analytics function in order to identify potential risk behaviors that may not be accounted for within our current surveillance framework. The selected candidate will help to lead the creation and development of this function:

  • Developing models to integrate and exploit multi-disciplinary data. The data sets likely to be leveraged include, but are not limited to:
  • Traditional structured sources (e.g., market and transactional data)
  • Network graphs, built using communication meta-data and referential information that might be indicative of embedded relationships
  • Communication content - the team is currently developing models to identify contextually relevant content, using advanced NLP techniques
  • Working with the Technology Organization (database administrators, data architects, Information Security, etc.) to propose and evaluate options for an optimal data infrastructure to facilitate analysis
  • Championing big data technologies throughout the division
  • Coordinating with Compliance Senior Management, Compliance Officers, and the Business to propose avenues of risk investigation
  • Tracking progress and managing deliverables against timelines
  • Delivering presentations to senior management, and other stakeholders, to communicate findings and recommendations
  • Working with surveillance investigative teams to escalate potential findings for further review
  • Coordinating with other constituents of the Surveillance Analytics Group in order to hand off requirements for new surveillances, when appropriate

Basic Qualifications
  • PhD in Computer Science, specializing in statistical modeling, machine learning, multivariate time-series and large-scale data analysis
  • 7+ years of relevant work experience
  • Proven ability to apply cutting-edge statistical techniques to large, complex data sets in order to solve business problems
  • Ability to balance technical expertise with functional/business understanding
  • Strong analytical and problem solving skills
  • Extensive knowledge of big data technologies/architectures (e.g., Hadoop, Pig, Hive, Mahout, etc.)
  • Experience with key analytics methods (e.g., machine learning, link analysis, predictive modeling, natural language processing, text mining, simulations, unstructured data analysis)
  • Familiarity with a broad range of database structures and data manipulation languages (e.g. SQL)
  • Expertise with statistical software packages and data mining tools (e.g., SAS, SPSS)
  • Working knowledge of financial markets & products
  • Effective verbal and written communications skills
  • Willingness to adapt in a fast-paced work environment; strong sense of urgency

Preferred Qualifications
  • Programming languages (C, C++, Java, R, etc.)
  • Experience managing a team
  • Client service experience (internal or external)
  • Experience working on a global team

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