Data Scientist - Cybersecurity

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

Visa's Cybersecurity team provides enterprise-wide, risk-based cybersecurity policies, practices, and solutions to protect Visa’s systems and data from internal and external threats. To protect Visa’s assets in this dynamic threat landscape, they are deploying new cyber-security tools, collaborating across industries, and taking a proactive approach to monitoring the cyberspace beyond the Visa network.

As part of Cyber Threat Analytics and Research team (CTAR) , you will leverage cutting-edge technologies to perform statistical profiling, inference, classification, clustering and predictive analysis. As a key member of the technical team, you will create and implement sophisticated machine learning models to help derive new insights to defend against cyber-attacks. You will be working with a large variety of data sets, cutting-edge security technologies, and world-class operation teams to create awesome analytics for security and other business units.

 

Essential Functions:

• Analyze cyber event logs using Spark and big data technologies and develop deeper insights into products using advanced statistical methods.

• Formulate cyber threat scenarios into technical data problems and develop high fidelity models to capture unseen threats

• Devise and implement deep learning models for building user behavior profiles. This includes data acquisition, feature engineering, model development, and deployment.

• Conduct feature engineering on various data sources to build and enrich feature store

• Fine tune open source LLM to detect anomalous user behavior

• Leverage Generative AI to perform RAG for helping improve Cyber investigation efficiency

• As a member of the CTAR team, you will work closely with other data scientists and data engineers to build, design, engineer, and develop analytical software and services that deliver security functionality and improve security efficiency and capabilities through automation.  

• Assist in shaping overall direction, life-cycle management, and leadership for Information Security architecture and technology related to Visa. 

• Communicate clean and persuasive data directly to end users, leadership, and other stakeholders, technical and non-technical.

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

Basic Qualifications:
•2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience

Preferred Qualifications:
•3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
•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