• Consumer Lending - Decision Science - Associate - Bengaluru

    Location(s) IN-Bengaluru
    Job ID
    2018-48952
    Schedule Type
    Full Time
    Level
    Associate
    Function(s)
    General, Quant/Strats
    Region
    India
    Division
    Consumer and Commercial Banking Division
    Business Unit
    Loans Data Science
    Employment Type
    Employee
  • MORE ABOUT THIS JOB

    Consumer and Commercial Banking (CCBD)

    Consumer and Commercial Banking Division brings innovative solutions to traditional banking activities. We are a global team of lenders, investors, risk managers, skilled marketers, web experts and banking specialists. We provide a suite of solutions to help our customers meet their personal financial goals. We make direct investments in, and manage risk of, a portfolio of corporate loans and securities. And we help transform distressed communities through investments and loans of private capital.

    Digital Finance Description

    Digital Finance, a business unit within CCBD, is comprised of the firm’s digitally-led consumer businesses, which include the Marcus deposits and lending businesses, as well as the personal financial management app, Clarity Money. Digital Finance combines the strength and heritage of a 149-year-old financial institution with the agility and entrepreneurial spirit of a tech start-up. Through the use of machine learning and intuitive design, we provide customers with powerful tools that are grounded in value, transparency and simplicity to help them make smarter decisions about their money.

    RESPONSIBILITIES AND QUALIFICATIONS

    Job Summary & Responsibilities :-

    • As part of the decision and data science function for Marcus lending business, one should be at the forefront of a data-driven initiative to optimize decision making. This role will draw upon knowledge of programming and Quantitative solutions. This role entails:
    • Rapidly prototype early-stage solutions and design / evaluate predictive models and advanced algorithms to drive business decisions throughout the customer lifecycle (prospecting, acquisition, underwriting, fraud, collections, enhancing customer experience)
    • Understand the systems and the business processes that populate those systems with data
    • Carry out data processing including statistical analysis, variable selection, and dimensionality reduction, custom attribute engineering, as well as the evaluation of new data sources
    • Leverage methods from diverse disciplines such as traditional modeling, machine learning, deep learning, artificial intelligence, statistical modelling, information theory, information retrieval and other areas to gain customer insights, draw conclusions and work with business partners to put those insights into action
    • Participate in data architecture decisions and partner with technology teams to implement models/algorithms in production
    • Help document your assumptions and methodologies, as well as carry out validation and testing to facilitate peer reviews and independent model validation
    • Think strategically on a higher level, proposing new business metrics or suggesting alternatives, creating highly interpretive models that imply new context and new semantics for data

     

    RESPONSIBILITIES AND QUALIFICATIONS

    Basic Qualifications

    • BS/MS or PhD in a quantitative field - Applied Mathematics, Physics, Engineering, Computer Science, Statistics, Econometrics and other Quantitative fields
    • Atleast 3 years of relevant experience for Associate, in prior model development in credit risk, marketing response modeling and Collections.
    • Strong programming background in compiled or scripting languages (C/C++, Python, R, Java, etc.)
    • Ability to explain complex models and analysis to diverse audience in a layman intuitive way

    Preferred Qualifications

    • Familiarity with advanced ML models - neural networks (feed forward, CNNs, RNNs, LSTM), Hidden Markov Models, random forests, SVMs, multivariate analysis, clustering, dimensionality reduction or participation in Kaggle type data science competitions
    • Experience with distributed computing (Hadoop, Spark)

    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.

    Options