• Competitive
  • Wilmington, DE, USA
  • Permanent, Full time
  • Citi-US
  • 2019-04-22

Fraud Risk Senior Analyst (Data Science Team Analyst - Fraud Advanced Analytics)

Fraud Risk Senior Analyst (Data Science Team Analyst - Fraud Advanced Analytics)

  • Primary Location: United States,Delaware,Wilmington
  • Education: Bachelor's Degree
  • Job Function: Risk Management
  • Schedule: Full-time
  • Shift: Day Job
  • Employee Status: Regular
  • Travel Time: Yes, 10 % of the Time
  • Job ID: 19013277


Description

About Citi

Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients.

Citi's Mission and Value Proposition explains what we do and Citi Leadership Standards explain how we do it. Our mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We strive to earn and maintain our clients' and the public's trust by constantly adhering to the highest ethical standards and making a positive impact on the communities we serve. Our Leadership Standards is a common set of skills and expected behaviors that illustrate how our employees should work every day to be successful and strengthens our ability to execute against our strategic priorities.

Diversity is a key business imperative and a source of strength at Citi. We serve clients from every walk of life, every background and every origin. Our goal is to have our workforce reflect this same diversity at all levels. Citi has made it a priority to foster a culture where the best people want to work, where individuals are promoted based on merit, where we value and demand respect for others and where opportunities to develop to are widely available to all.

About Global Consumer Bank

Citi's Global Consumer Bank (GCB), a global leader in credit cards, wealth management and commercial banking, serves as a trusted partner to more than 110 million customers in 19 countries worldwide, providing financial services that enable growth and economic progress. The Global Consumer Bank operates four business lines - Branded Cards, Retail Services, Retail Banking and Commercial Banking - in three priority markets: Asia, Mexico and the U.S. Over the past few years, our business has transformed to become a simpler, leaner, focused franchise.
Citi is on a journey to become a world-class digital bank has tangibly accelerated with a mobile-first strategic focus and deployment of a new, agile operating model fostered massive improvements in the design and delivery of digital features and in the customer experience. As a result the franchise has seen significant growth in the number of digital users, mobile downloads and digital engagement.  

About the GCB Fraud Prevention Organization

The financial crimes environment continues to be challenging, with cybercrime worldwide remaining highly lucrative and criminals becoming more organized and sophisticated, making it harder to distinguish between real and fraudulent customers. To combat the agile threat, the Global Consumer Bank (GCB) Fraud Prevention organization operates leveraging an intelligence-led, threat driven model that targets fraud along the entire fraud lifecycle, enabling the integration of analysis, dissemination of information and coordination of action with speed and agility across businesses and regions.


Fraud Risk Senior Analyst (Data Science Team Analyst)

Role & Responsibilities:

The Fraud Advanced Analytics - Data Science role resides in GCB Fraud Prevention's Global Fraud Analytics & Model Management team and is responsible for leveraging the latest analytical tools and techniques to enhance fraud detection and mitigation capabilities for consumer businesses, advancing the bank's ability to detect potential fraud by solving challenging analytical problems. Key Responsibilities include: 
  • Drive complex data science solutions using multiple data sources, including data acquisition, model development, and production deployment.
  • Model development leveraging supervised and unsupervised methods and diverse and massive data sources.
  • Development of a comprehensive knowledge of Citi data and core fraud systems.
  • Actively collaborate with cross-functional business partners and analytics teams to design and generate advanced analytics and machine learning solutions.


Qualifications

Education & Experience:
  • Bachelor's degree required (Master's degree preferred) in statistics, mathematics, engineering, computer science, physics, economics, or related quantitative discipline.
  • 5-8+ years-experience, with 3+ in fraud, risk management or other relevant experience in analytics and modeling.
  • Strong understanding of statistical modeling, data mining concepts, machine learning, and experience in solving complex problems with these disciplines.

Skills:
  • Proficient in SAS/SQL, MS Office, programming languages (e.g. Python, R), analytical tools (Enterprise Miner, Knowledge Studio, H2O, Tableau) and big data tools (e.g. Hadoop HDFS/YARN, Kafka, Hive, Spark).
  • Strong quantitative and analytic skills and data-driven mindset; ability to derive patterns, trends and insights, and perform risk/reward trade-off.
  • Extremely detail-oriented; intellectual curiosity.
  • Constantly seeks clients' feedback and holds himself/herself accountable for listening to and learning from clients.
  • Good written and verbal communication skills, with ability to connect analytics to business impacts; comfortable presenting to peers and management.
  • Ability to multi-task and work against tight deadlines.
  • Ability to work independently with baseline instructions/guidelines from management.