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.
About the Role:
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 Principal 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.
Essential Functions:
Research and develop 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.
Basic Qualifications:
• 12 or more years of work experience with a Bachelor’s Degree or at least 10 years of work experience with an Advanced degree (e.g. Masters/MBA /JD/MD), or a minimum of 5 years of work experience with a PhD
Preferred Qualifications:
• 15 or more years of experience with a Bachelor’s Degree or 12 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, or MD), PhD with 9+ years of experience 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.
• 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.
• Experience in payments, fraud or credit risk management or related industry is a plus.
• 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.
Work Hours: Varies upon the needs of the department.
Travel Requirements: This position requires travel 5-10% of the time.
Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.
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.
Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.
U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 183,400.00 to 266,050.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.
Yearly based
Austin, TX, United States