CIMD - Marcus by Goldman Sachs - Fraud Data Science - Analyst/Associate - Bengaluru



Consumer and Investment Management (CIMD)

The Consumer and Investment Management Division includes Goldman Sachs Asset Management (GSAM), Private Wealth Management (PWM) and our Consumer business (Marcus by Goldman Sachs). We provide asset management, wealth management and banking expertise to consumers and institutions around the world. CIMD partners with various teams across the firm to help individuals and institutions navigate changing markets and take control of their financial lives

Consumer

Consumer, externally known as Marcus by Goldman Sachs, is comprised of the firm's digitally-led consumer businesses, which include our deposits and lending businesses, as well as our personal financial management app, Clarity Money. Consumer combines the strength and heritage of a 150-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

Responsibilities And Qualifications

Your Impact

We are seeking an experienced fraud strategy leader for the consumer products and services. This leader will develop, deliver, and manage our fraud risk management strategy, machine learning models, capability and process within the consumer business of Goldman Sachs. This individual will have a direct and material impact on company financials and fraud risk net write-off goals. The candidate will work closely with technology, product and operations teams to identify ways to enhance fraud infrastructure, tools and processes to enable a secure and seamless experience for our customers while managing fraud loss and addressing existing and emerging fraud trends. This role will require the candidate to have an in depth understanding of fraud risks and keep up-to-date with new approaches for managing risks through the application of technology, processes, and people.

Job Summary and Responsibilities

  • Ability to lead projects for developing fraud strategies and machine learning predictive models
  • Manages projects from end to end design, development and implementation
  • Good understanding of predictive models and data science techniques
  • Manages team of data scientists that are from both data science and strategy background to deliver fraud initiatives
  • Drives continuous improvement of key fraud metrics
  • Collaborates with key partners and leadership to define and prioritize business needs to inform strategies
  • Work directly with the Customer Operations leadership team responsible for execution of the fraud strategy
  • Ability to communicate complex analytical ideas effectively and persuasively


Qualifications
  • Strong data analytical skills, problem solving and technical skills
  • Demonstrated proficiency in core elements of data mining and analysis using large data sets
  • Previous experience leading data science or strategy team
  • Strong project management skills and attention to details
  • Proficiency in Python, R, Java, SQL is a plus
  • Decision sciences experience a plus
  • Fraud risk experience is a plus
  • Education Qualifications: Minimum Undergraduate Degree in Business Administration, Statistics, Economics / Econometrics, engineering or any other computationally extensive discipline.
  • Graduate Degree preferred


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.


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