# Staff Data Scientist at Visa

Visa is hiring a Staff Data Scientist in Bellevue, United States. It pays $141k-$226k a year and Level rates it Builds AI ●●●●; you can [apply on Visa](https://jobsbylevel.com/go/4ac8734c-6423-4c13-9698-c186d68b27ea?utm_medium=ai-agent).

AI Level 4, AI centrality 84 out of 100. US - Bellevue, WA.

## Details

- Company: [Visa](https://jobsbylevel.com/companies/visa)
- AI level: AI Level 4 (score 84 out of 100)
- Location: US - Bellevue, WA
- Salary: $141k-$226k
- Posted: June 10, 2026
- Apply: https://jobsbylevel.com/go/4ac8734c-6423-4c13-9698-c186d68b27ea?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=staff-data-scientist-at-visa-a47914

## Prepare for this job

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## Description

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

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