Experian

Fraud Analytics Intern

Job Description

Posted on: 
December 12, 2023

Experian Fraud and ID analytics team is an Experian division formed to combat all kinds of fraud that our financial, telecom, and other credit issuer clients’ or non-credit issuer clients’ experience. Experian® is a global leader in providing information, analytical tools and marketing services to organizations and consumers to help manage the risk and reward of commercial and financial decisions. Using our comprehensive understanding of individuals, markets, and economies, we help organizations find, develop and manage customer relationships to make their businesses more profitable.

Experian’s Summer Internship Program is a unique opportunity for students across the country to gain hands-on work experience in our innovative global company. Our interns work alongside Experian employees to tackle meaningful projects and gain valuable skills in their chosen field. During our summer internship program, interns will have access to the latest technologies and challenging work. As a summer intern, you’ll learn about our exciting financial inclusion products and programs, experience philanthropic events that make us a force for good, and network across our global business units. Get ready to discover the unexpected as a part of our #uniquelyexperian summer internship program.

Responsibilities

Responsibilities of the Fraud Analytics Intern include:

Job Requirements

  • Currently enrolled in a minimum of a Bachelor’s degree program in Computer Science/Engineering, Data Science, Electrical Engineering, Mathematics, Statistics, or related field
  • Be returning to school in the Fall of 2024 to complete degree program
  • Proficient in Python, PySpark, JAVA, Scala or C/C++
  • Familiarity with Unix and scripting languages and version control tools (such as git)
  • Knowledge with cloud computing services (AWS, etc)
  • Able to quickly understand technical and business requirements and be able to translate into technical implementation.

Preferred Qualifications:

  • Knowledge on analytics and machine learning
  • Past work on large size datasets
  • statistical modeling / data analysis or financial services industry experience
  • Basic knowledge concerning with Hadoop and NoSQL related technologies such as Map Reduce, Spark, Hive, Pig, HBase, mongoDB, Cassandra, etc.
  • Knowledge in SAS

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