Jobs
Benefits & Perks
•Healthcare
•Dental
•Vision
•401(k)
•FSA/HSA
•Life Insurance
•Paid Time Off
•Wellness Program
•Bonus
•Equity
•Healthcare
•401k
•Equity
Required Skills
Machine Learning
Data Science
Python
Big Data
ETL
Experimentation
Model Evaluation
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
We are looking for a versatile, curious, and highly technical Lead Applied Scientist to shape the future of AI and data products across the Visa Acceptance Platform. You will partner with engineers, product leaders, and AI researchers to design, deploy, and scale advanced machine learning solutions across a global ecosystem.
In this role, you will:
- Define technical strategy for AI/ML models supporting global payments and next-generation agentic commerce experiences.
- Mentor a high-performing team and establish best-in-class practices for data science, MLOps, and model governance.
- Lead end‑to‑end development of large-scale data solutions—from data extraction through modeling, deployment, and monitoring.
- Drive platform transformation initiatives that enhance delivery efficiency, improve model performance, and enable new product opportunities.
What You Will Do (Essential Functions)
- Provide technical leadership in designing scalable, maintainable, and secure data science solutions; set standards for modeling, coding patterns, and MLOps.
- Lead efforts to improve data extraction, data quality, lineage, and governance, partnering with engineering teams across the platform.
- Develop strategies for wrangling, modeling, and leveraging high-volume structured and unstructured data using modern AI/ML techniques.
- Guide conversations with Product, Cybersecurity, and Engineering to clarify complex business and technical requirements and ensure secure deployment.
- Identify emerging patterns across massive datasets to influence platform‑wide enhancements, roadmap decisions, and AI-driven product improvements.
- Drive modernization opportunities including software upgrades, security patches, and infrastructure improvements.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Qualifications
Basic Qualifications
- 10+ years of relevant work experience with a Bachelor’s Degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience.
Preferred Qualifications
-
12+ years of relevant work experience with a Bachelor’s Degree in Computer Science or Data Science or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience.
-
3+ years building and deploying AI/ML models for predictive analytics or insights.
-
4+ years working with large-scale data technologies such as Hadoop, Hive, Kafka, Spark, Redis, NoSQL, or RDBMS.
-
2+ years designing and maintaining ETL or data pipelines.
-
Experience working with Big Data, distributed computing, and streaming/real-time systems.
-
Strong experience in metrics design, experimentation, and model evaluation.
Additional Information
Work Hours: Varies upon the needs of the department.
Travel Requirements: This position requires travel 5-10% of the time.
Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.
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.
Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.
U.S. APPLICANTS ONLY: The estimated salary range for this position is 180,000.00 to 288,000.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. 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.
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About Visa
Reviews
2.0
3 reviews
Work Life Balance
1.5
Compensation
2.0
Culture
1.2
Career
1.8
Management
1.3
10%
Recommend to a Friend
Pros
Active recruiting for senior positions
Work authorization support for spouses
Opportunity to seek external roles
Cons
Toxic work environment
Below-market compensation offers
Poor management and leadership
Salary Ranges
23 data points
Junior/L3
Mid/L4
Junior/L3 · Analyst
1 reports
$106,195
total / year
Base
$92,300
Stock
-
Bonus
-
$106,195
$106,195
Interview Experience
4 interviews
Difficulty
3.3
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 75%
Negative 25%
Interview Process
1
Application Review
2
Online Assessment
3
Phone Screen
4
Technical Interview Rounds
5
Final Round Interview
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
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