Posted:2 days ago|
Platform:
On-site
Full Time
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.
We are looking for a Staff ML Scientist to design and develop next‑generation AI and ML models that solve real‑world challenges in the payments ecosystem covering transaction monitoring, fraud detection, and risk mitigation across multiple Visa businesses. You will be part of cross-functional team of data scientists and ML engineers based out of Bangalore and collaborating globally, driving innovation in the Risk and Identity Solutions (RaIS) through advanced AI/ML technologies.
You will combine deep technical expertise with ownership, velocity, and influence. You will drive the scientific roadmap at scale, ensuring models are aligned, explainable, and robust, and you’ll collaborate with world‑class experts while influencing product strategy in a high‑stakes domain. The position offers access to top‑tier compute, tools, and datasets, and a collaborative, innovative culture focused on shaping the future of global payments.
Responsibilities
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Preferred Qualifications –
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.
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