Job Description Visa has the world’s largest consumer payment transaction data set.  And we leverage the billions of transaction records to help our clients in the payment ecosystem grow their businesses and to help consumers access a fast, safe, and rewarding payment experience. From across the globe, people are increasingly relying on digital payments and mobile technology to use their money any time, make purchases online, transfer funds across borders and access basic financial services. Risk and Identity Services (RaIS) is a technology organization at Visa that builds products and services for our clients that ensures the security and reliability of these payments. We have invested heavily in advanced authentication and fraud prevention technologies, to fight fraud, enable acceptance, and support consumers.   We are looking for a Sr. Staff ML Scientist to lead our machine learning initiatives in RaIS and drive innovation in Visa's strategic products and services. As a key member of our Applied ML research and development team, you will be responsible for designing, developing, and deploying machine learning models on cloud platforms to solve complex problems and drive innovation in our products and services.   This role represents an exciting opportunity to make key contributions to Visa's strategic vision as a world-leading data-driven company. The successful candidate must have strong academic track record and demonstrate excellent software engineering skills. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.   Responsibilities:

• Applied research and development of machine learning algorithms and models to address business challenges and improve product performance.
• Collaborate with cross-functional teams including data engineers, software developers, and product managers to understand requirements and design scalable solutions.
• Implement machine learning pipelines and workflows for data preprocessing, feature engineering, model training, and evaluation.
• Optimize machine learning models for performance, scalability, and reliability in cloud environments.
• Deploy machine learning models to cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure. Develop monitoring and alerting systems to track model performance and detect anomalies.
• Collaborate with DevOps teams to automate deployment processes and ensure smooth integration with existing systems.
• Stay updated with the latest advancements in machine learning, cloud computing, and deployment technologies, and apply them to improve our practices and solutions.
• Communicate technical concepts and findings to both technical and non-technical stakeholders.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs. Qualifications Basic Qualifications: • MS/PhD degree in computer science, computer engineering, mathematics, or equivalent field with a focus on artificial intelligence/machine learning. • Experience in ML application development, and deployment, with a track record of delivering impactful solutions in a fast-paced environment. • 3+ years of leading and mentoring teams • Proficiency in programming languages such as Python, and experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn. Experience with cloud platforms such as AWS, GCP, or Azure, and proficiency in deploying machine learning models using cloud services. • Demonstrated ability to think outside the box and innovate. Strong problem-solving skills and ability to thrive in a dynamic and fast-changing environment. • Strategic mindset with the ability to think creatively and identify opportunities for applying machine learning to solve business problems and drive innovation. • Demonstrated ability to think outside the box and innovate. Strong problem-solving skills and ability to thrive in a dynamic and fast-changing environment. • Excellent communication and interpersonal skills, with the ability to influence and inspire cross-functional teams and senior leadership. Preferred Qualifications: • Experience with big data technologies (e.g., Spark, Hadoop) and distributed computing. • Knowledge of reinforcement learning, deep learning, and natural language processing (NLP) techniques. • Experience with MLOps practices and tools for model monitoring, versioning, and governance. • Experience in payments, fraud or credit risk management or related industry is a plus. Additional Information 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.