Data Scientist, Predictive Fraud Intelligence

Visa • Atlanta, GA

14h • Hybrid

About The Position

As part of Visa Predictive Fraud Intelligence team (PFI), you will leverage cutting-edge technologies to perform statistical profiling, inference, classification, clustering and predictive analysis. As a key member of the data science team, you will create and implement sophisticated machine learning models to help derive new insights to defend against fraud attempts.
You will be working with a large variety of data sets, cutting-edge analytical technologies, and world-class operation teams to create awesome analytics for security and other business units.
Your responsibilities include:
Analyze transaction event logs using Spark and big data technologies and develop deeper insights into products using advanced statistical methods.
Devise and implement deep learning models for building user behavior profiles. This includes data acquisition, feature engineering, model development, and deployment.
Support and optimize other existing analytical models/products.
Maintain the backend operations pipeline, including the job scheduler and data processes.
Devise and implement methods for efficiently monitoring model effectiveness and performance in production.
Use GenAI to create an agentic framework that enhances fraud detection efficiency.
As a member of the PFI team, you will work closely with other data scientists and data engineers to build, design, engineer, and develop analytical services that deliver fraud detection abilities and improve the efficiency and capabilities through automation.
Communicate clean and persuasive data directly to end users, leadership, and other stakeholders, technical and non-technical.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Requirements

• Bachelor's degree, with 1-2 years of relevant work experience
• 1-2 years of relevant work experience with either bachelor’s or master’s degree in data science, mathematics, statistics, economics, computer science, engineering, or other related business or quantitative discipline is required.
• Solid background and hands on experiences with building Machine learning, deep learning and AI models.
• Experience with Generative AI/LLM Excellent understanding of algorithms and data structures and proficiency in Python and SQL.
• Experience working with large datasets using tools and Hadoop, Spark, or Hive. Excellent analytic and problem-solving capability combined with ambition to solve hard problems. Strong communications skills and ability to collaborate. Highly driven, resourceful and results oriented. Good team player and excellent interpersonal skills. Demonstrated ability to lead and navigate through ambiguity.

Nice To Haves

• 2 years of work experience.

Responsibilities

• Analyze transaction event logs using Spark and big data technologies and develop deeper insights into products using advanced statistical methods.
• Devise and implement deep learning models for building user behavior profiles. This includes data acquisition, feature engineering, model development, and deployment.
• Support and optimize other existing analytical models/products.
• Maintain the backend operations pipeline, including the job scheduler and data processes.
• Devise and implement methods for efficiently monitoring model effectiveness and performance in production.
• Use GenAI to create an agentic framework that enhances fraud detection efficiency.
• As a member of the PFI team, you will work closely with other data scientists and data engineers to build, design, engineer, and develop analytical services that deliver fraud detection abilities and improve the efficiency and capabilities through automation.
• Communicate clean and persuasive data directly to end users, leadership, and other stakeholders, technical and non-technical.

Benefits

• Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level