• Risk - Operational Risk Management and Analysis - Data Analytics - Associate/ Vice President - Bengaluru

    Location(s) IN-Bengaluru
    Job ID
    Schedule Type
    Full Time
    Business Unit
    Operational Risk
    Employment Type


    The Risk division is responsible for credit, market and operational risk, model risk, independent liquidity risk, and insurance throughout the firm.


    Operational Risk Management and Analysis

    Operational Risk Management and Analysis (ORMA) is an independent risk management function, responsible for developing and implementing a standardized framework to identify, measure, and monitor operational risks across the firm.


    The Quantification function within ORMA drives capital planning and stress testing, quantifies inherent and residual risk, develops quantitative risk assessment processes, engages with the firm's businesses to understand their risk profile, and delivers reports to regulators and senior management.


    What is a Strat?

    Members of Goldman Sachs’ strategist (‘Strat’) job function develop quantitative and technological techniques to solve complex business problems. Working within the firm’s Risk, Sales and Trading, Investment Banking, and Investment Management Divisions, Strats use mathematical and scientific knowledge to create financial products, advise clients on transactions, measure risk, and identify market opportunities.


    What Will Your Impact Be?

    As a Strat within the Risk Division, you will play an integral role in managing the operational risk of the firm using quantitative approaches. You will be using the latest open source and internal technologies to develop automated risk insight generation programs, as well as design state-of-the-art systems to meet the increasingly complex operational risk exposures that the firm faces.  You will apply a variety of machine learning techniques to model algorithmic trading risk, information and cyber security risk, third party risk, and other top risk domains to derive actionable insight for the firm’s leadership.


    What Is the Team’s Impact?

    You will be part of the Data Analytics team in Bengaluru which has primary responsibility for building out a world class analytics program from first principles, developing scalable data models for solving a variety of analytics problems, reporting risk management insights, and developing analytics tools. The mission of the team is to enhance the effectiveness of risk management by using concepts from the statistical, mathematical, and computational world to measure operational risk.


    What Are Your Responsibilities?

    Develop and validate quantitative models to:

    * Model operational risk quantitatively using Bayesian networks, extreme value distributions, Monte Carlo simulations, and other techniques in order to continuously improve and develop new models for evolving risks

    * Develop KRIs and 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

    * Develop trigger-based assessment models using multiple datasets to improve subjective assessment reliability, process robustness, and effectiveness

    * 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

    * Design customized anomaly detection algorithms for use on large and diverse data sets in order to analyze drivers for materialized risks and control failures

    * Engage directly with senior leadership to develop team strategy, assess new activities and develop proofs of concept, enforce limits, comply with regulatory requirements, and challenge existing methodologies

    * Provide advisory support; identify and test new quantitative risk measures

    * Integrate new information and data sets into the firm’s Enterprise Data Lake


    Design and develop sophisticated operational risk management programs, requiring you to:

    * Develop platforms for the presentation of a unified picture of operational risk for senior management and business divisions, enabling real-time analytics-driven interventions

    * Partner with business divisions across the firm to develop analytical solutions and systems for analyzing and measuring specific risk exposures


    What Methods and Concepts Will You Employ?

    * Bayesian networks and inference for modeling risk

    * Classification problems using decision trees, logistic regression, and naïve Bayes

    * Recommendation engines using complex text and document similarity analysis

    * Clustering techniques including hierarchical, k-means, and spectral clustering and variants

    * Time series forecasting techniques from decomposition to AutoRegression Integrated Moving Average (ARIMA), and neural networks

    * Text mining and NLP with applications like topic modeling using latent Dirichlet allocation (LDA), latent semantic analysis, document clustering, et al.

    * Stochastic calculus and quantitative modeling for risk metrics, assessments, and events


    What Experience Will You Gain?

    * As a growing and maturing function, the role will provide first-hand experience in building a quantitative team providing you with a holistic view of the complete analytics development curve

    * Exposure to challenging quantitative problems

    * Development of quantitative and programming skills as well as product- and risk-specific knowledge

    * Involvement in critical internal risk management practices, both internally- and externally-facing

    * Myriad opportunities to work with other quantitative and business functions within the firm


    What Do We Need from You?

    * A degree in a quantitative field (computer science, applied mathematics, engineering, or related quantitative disciplines), and a keen analytical mind

    * Basic applied statistics, machine learning techniques (supervised and unsupervised), and usage of relevant algorithms and concepts

    * Depth of experience in algorithms and programming (Python, R, Java, C++, Matlab, et al.)

    * Experience with data visualization toolsets (Tableau, Spotfire, QlikView, R Shiny)

    * Experience with handling large data sets and building systems

    * Minimum of three years’ working experience in an analytical or technical role

    * Effective and clear written and verbal communications skills


    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.