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Staff Data Scientist

$145.3k - $232.7k
Full-time

VISA

About Us
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.

Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.

Job Description

Visa’s Post Purchase organization is building AI-driven decision intelligence across dispute resolution and recovery products, including RDR, CDRN, VDRN, and Recover. We are seeking a Staff Data Scientist to lead high-impact machine learning initiatives that improve automation, recovery outcomes, and client experience at global scale.

This is a Staff-level individual contributor role for someone who thrives in ambiguity, owns complex problem spaces, and drives solutions from concept through production with measurable business impact. You will work with large-scale transactions and dispute data to develop models that enhance decision quality and enable scalable, intelligent systems.

Key Responsibilities

  • Define and lead high-impact ML initiatives across dispute decisioning, merchant matching, and recovery prediction
  • Own end-to-end ML lifecycle, including problem framing, feature engineering, model development, deployment, and monitoring
  • Build and productionize scalable models using large-scale transaction and dispute datasets
  • Partner closely with Product, Engineering, and Data Engineering to translate business needs into data-driven solutions
  • Drive adoption of ML solutions through explainability, performance measurement, and stakeholder alignment
  • Develop experimentation frameworks to evaluate and continuously improve model performance
  • Design and implement GenAI/LLM-based solutions for explainability, workflow automation, and decision support
  • Influence product strategy by identifying opportunities to improve automation, efficiency, and customer outcomes
  • Mentor junior team members and contribute to best practices across the data science organization

Work Environment

Visa requires employees to work in the office 3 days per week. Specific expectations will be confirmed by the Hiring Manager.

Qualifications

Basic Qualifications:

  • 5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience
  • Experience with digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work

Preferred Qualifications:

  • 6+ years of experience with a Bachelor’s degree or 4+ years with an Advanced degree or up to 3 years with a PhD
  • Advanced degree (MS or PhD) in AI, Computer Science, Statistics, Operations Research, or a related quantitative field
  • Experience applying data science or analytics solutions to solve complex business problems with measurable outcomes
  • Proven track record of commercializing analytical or ML solutions in production environments
  • Strong experience managing or leading end-to-end projects across cross-functional teams
  • Agile experience and ability to manage evolving priorities in dynamic environments
  • Experience working with large-scale datasets and building scalable models
  • Experience with distributed data processing frameworks (e.g., Hadoop, Hive, Spark)
  • Proficiency in programming languages such as Python or R, along with SQL
  • Experience with version control tools such as git or GitHub
  • Hands-on experience applying machine learning and predictive modeling tecniques to business problems
  • Experience in data science, data engineering, or analytics roles in large-scale environments
  • Experience in payments, fraud, risk, disputes, fintech, or transaction-heavy domains
  • Experience working in global organizations with distributed stakeholders
  • Proven ability to lead projects, influence teams, and provide technical thought leadership

What Sets This Role Apart

  • Ownership of high-impact, ambiguous problem spaces across Visa’s Post Purchase ecosystem
  • Direct influence on ML-driven decision intelligence and product strategy
  • Opportunity to build scalable systems that improve recovery outcomes, automation, and client experience
  • Work at the intersection of AI/ML, product, and platform at global scale

U.S. Applicants Only

The estimated salary range for this position is $145,300.00 to $ 232,700.00 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.

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 protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
Vacancy posted 8 days ago
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