• Associate - RSK3858421

    Location(s) US-NJ-Jersey City
    Job ID
    Schedule Type
    Full Time
    Business Unit
    Risk Engineering
    Employment Type

    Associate with Goldman Sachs & Co. LLC in Jersey City, NJ.


    Work Schedule: 40 hours per week (9:00 a.m. to 6:00 p.m.)


    Duties: Associate with Goldman Sachs & Co. LLC in Jersey City, NJ. Develop and validate quantitative models to identify, measure, and monitor operations risks across the firm. Develop Key Risk Indicators (KRIs) and Key Control Metrics (KCMs) that reliably estimate operational risk exposure, control effectiveness and other parameters of interest, such as algorithmic trading risk, information and cybersecurity risk, insider threat and fraud risk, and insurance effectiveness and optimization. Use Natural Language Processing (NLP) and linguistic techniques to derive actionable insights from a variety of sources of internal and external operational risk events, assessment information, and publicly-available data. Monitor and enforce operational risk limits and risk appetite, comply with regulatory requirements and challenge existing methodologies. Engage directly with risk and technology leadership to architect and drive cohesive risk measurement platform strategy; develop platforms for the presentation of a unified picture of operational risk for senior management and business divisions and enable real-time analytics-driven interventions. Provide advisory support and partner with risk specialists to identify and test new quantitative risk measures across the breadth of operational risk in order to measure risk exposures. Integrate new information and data sets into the firm’s Enterprise Data Lake (a Hadoop HDFS- and Sybase IQ-based data warehouse). Design logical domain models to represent key operational risk concepts and develop transformation logic to refine raw data sources for integration with them. Apply data assurance principles outlined within the Basel Committee on Banking Supervision (BCBS) 239 Principles for effective risk data aggregation and risk reporting documentation; Ensure completeness, timeliness, and accuracy of quantitative measurements and their inputs. Mentor and train junior staff in core technical skills; support swiftly-growing team in a nascent risk quantification discipline. Must be willing to work with proprietary technologies. No knowledge of proprietary technologies is required pre-hire.


    Job Requirements: Bachelor’s degree (US or foreign equivalent) in Computer Science, Computer Systems, or a related quantitative discipline. Three (3) years of experience in the job offered or in a related role. Must have one (1) year of experience with: structured data retrieval, data analysis, and data modeling using SQL, Python, and Java; development of scripts and calculations necessary for risk measurement through KRIs and KCMs using Python and Scala; Algorithms and programming: Java; interactive data visualization development and insight generation using Tableau Desktop and Tableau Server; Technology platform strategy and requirements design utilizing Microsoft PowerPoint and Visio; Technology project management: Microsoft Project and Excel; sourcing, transforming, and producing enterprise-scale data sets (billions of rows of data) by utilizing Hadoop MapReduce and Apache Spark; engaging in risk analysis, data analysis, and synthesis of cogent results for consumption by both technical and non-technical senior executives; logical data model design to represent key risk concepts, including experience developing transformation logic to refine and integrate raw data sources into logical concepts; and application of data assurance principles outlined within the Basel Committee on Banking Supervision (BCBS) guidelines, including experience with techniques for ensuring completeness, timeliness, and accuracy of quantitative measurements and their inputs. Must have six (6) months of experience with: analysis of unstructured text data for derivation of structured content, using natural language processing (NLP) methodologies; and basic applied statistics, machine learning techniques (supervised and unsupervised), and usage of relevant algorithms and concepts.


    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., 2019. All rights reserved
    Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.