About UsVisa 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 DescriptionSr. 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).Ensure reproducibility and quality in analytic pipelines and project deliverables.Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.QualificationsBasic Qualifications:5 or more 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)Experience in developing advanced data science models and applying machine learning / deep learning (ML/DL) techniques to business problems.Experience in managing data science projects from scoping to delivery.Experience in LLM usage to improve the quality of solutions and day-to-day work.Experience in extracting and aggregating data from large data sets using SQL or other tools.Experience in creating reproducible analytic pipelines.Experience in working with modern distributed systems, including Hadoop, Hive/SQL, and Apache Spark.Experience in collaborating with cross-functional teams to deliver scalable solutions.Experience in communicating complex technical concepts to business audiences.Experience in leading project teams and providing technical direction.Preferred Qualifications:Extensive experience working in the data science, data engineering, or analytics profession.Hands-on experience working with extremely large data sets and building scalable models.Experience in data visualization using Tableau, Power BI, or R/Python.Expertise in multiple programming languages (e.g., Python, R, Spark).Previous exposure to payments industry / Fraud detection is a plus but not mandatory.Experience working in global organizations and collaborating with stakeholders across geographies.Visa is an EEO EmployerQualified 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.