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Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.


Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.



Job Description

The Anomaly Detections Platforms (ADP) is a global team tasked with the role of developing data driven fraud detection solutions to identify abnormal transaction trends and work closely with Risk Operations Center (ROC) to support in fraud mitigation.


This position will support the Anomaly Detection Platforms team drive several of Visa’s most important and high-visibility fraud deterrence projects within Global Risk’s Payment Fraud Disruption (PFD) team. This fast-paced team of technology experts identifies and supports mitigating attacks targeting the global payment ecosystem. Key measures of success for this position include the ability to develop and automate key attack intelligence capabilities that optimize detection of fraudulent anomalies. The primary responsibilities for this role will include:


  • Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, data mining and statistical techniques.
  • Develop predictive and prescriptive solutions, leveraging AI/ML and SPC, that monitor and detect various fraud schemes and abnormal transaction activity.
  • Lead global team of analytical professionals to write the next chapter of Visa’s fraud detection capabilities. 
  • Be an expert at getting to the root of a problem, defining business objectives and formalizing data requirements – especially in a fast paced, fluid environment.
  • Develop real-time and batch processed customized monitoring solutions to enable clients take proactive action to fraud threats.
  • Analyze complex financial data to uncover patterns, anomalies, and insights that support risk assessment and fraud identification.
  • Collaborate with Technology partners to enhance fraud detection capabilities for improved insights and pattern detection.
  • Mentor and train other team members on key solutions
  • Ability to work on multiple projects and initiatives with different/competing timelines and demands.
  • Be an out-of-the-box thinker who is passionate about brainstorming innovative ways to use our unique data to answer business problems.
  • Provide guidance in modern analytic techniques and business applications to unlock the value of Visa’s unique data set, in keeping with market trends, client needs and emerging techniques.

SECONDARY RESPONSIBILITIES:


  • Collaborate with Payment Systems Intelligence and Risk Operations Center (ROC) teams to recognize and implement measures to identify and disrupt new fraud and cybercrime threats to the clients enrolled in the Fraud Services program.
  • Provide intelligence and technical analysis support to the Global Risk organization to further protect the payment ecosystem.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.



Qualifications

REQUIRED:
• Ability to conduct complex analytical functions by performing fraud assessments and analyzing criminal methods.
• Knowledge of transactions, systems processing transactions and overall transaction process.
• Proficiency in Python, SQL and Splunk for data manipulation, analysis, and visualization.
• Extensive experience with data preprocessing, feature engineering, and model optimization for risk and fraud detection.
• Adaptable and able to work well in a fast paced, team-oriented environment.
• 6 years’ experience in payment card or information security industry, investigating payment card, cybercrime fraud / red team testing or bachelor’s degree in strong technical area with some real-word experience (e.g., internship)
• Passion for fraud schemes and cybercrime investigations
• Good interpersonal, facilitation, and demonstrated emerging leadership skills.
• Able to operate at an advanced level of written and spoken communication, write and speak effectively with impact.
• Highly adaptive, comfortable working within a complex, and often ambiguous, environment. Equally capable of thriving with changing circumstances, and to lead through the noise.
• Self-starter who can responsibly advance work and is comfortable making sound, well-informed judgement calls for progress, without needless delays.
• Experience standing up new functions and processes in highly complex and collaborative global environments.
• Capable of delivering presentations and comfortably interacting with all levels of Visa and client management
• Moderate understanding of networks, risk management, network security, digital forensics, and security operations
• High level of self-motivation and initiative
• 12 + yrs experience, Bachelor’s degree in relevant subject area required.
PREFERRED EXPERIENCE:
• Direct experience with VisaNet, ISO 8583, transaction routing, VCMS, Base I and Base II platforms.
• Concepts, terms, processes, policy, and implementation of information security



Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.




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