Senior Data Scientist

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

Sr. Data Scientists at the Consultant / Manager level are responsible for developing advanced data science models and leading technical project teams. The role requires hands-on experience with large-scale data sets, building scalable models, and applying machine learning and statistical techniques to solve business problems. The position involves collaborating with cross-functional teams, translating analytics output into actionable recommendations, and communicating complex concepts to diverse audiences.

All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.

Key Responsibilities:

- Develop and implement advanced data science models, including deep learning, machine learning, recommendation systems, and generative models.

- Lead and provide direction to technical data science teams, ensuring high-quality and rigorous project outcomes.

- Collaborate with cross-functional teams (product, engineering, marketing) to gather requirements and deliver scalable solutions.

- Translate analytics output into actionable business recommendations and communicate results to senior business audiences.

- Manage end-to-end data science projects, including planning, organizing, and delivering results with diverse teams.

- Work with real-world, large-scale data sets to build and deploy scalable models.

- Utilize modern distributed systems and data science tools (e.g., Hadoop, Hive/SQL, Apache Spark, TensorFlow, PyTorch, scikit-learn).