Job Description:

Team Summary:

The Risk and Identity Solutions (RaIS) team provides risk management services for banks, merchants, and other payment networks. Machine learning and AI models are the heart of the real-time insights used by our clients to manage risk. Created by the Visa Predictive Models (VPM) team, continual improvement and efficient deployment of these models is essential for our future success. To support our rapidly growing suite of predictive models we are looking for engineers who are passionate about managing large volumes of data, creating efficient, automated processes and standardizing ML/AI tools.

Technical Leadership

• Provide technical leadership and oversight to software architects, engineers, and data scientists.
• Drive the architecture for key cross-team/cross-product development projects.
• Establish software development and data science best practices via examples and shipping code.
• Ensure engineering and data science excellence (quality, security, performance, scalability, availability, resilience).

Collaboration & Strategy

• Collaborate with Product Office, Operations & Infrastructure, Cybersecurity, Client Support, and other Product Development teams to develop complete solutions.
• Drive the coordination, organization, and execution of qualitative and quantitative decisions.
• Guide the delivery of strategic projects aligned with business strategy on innovative payment acceptance and integrated commerce management.
• Collaborate closely with the global product teams in marketing and loyalty to define strategy and communicate a clear vision for the team.

Development & Innovation

• Deliver products with complex technical interdependencies by collaborating with geographically dispersed teams.
• Develop architectures that are inherently secure, robust, scalable, modular, API-centric, and global.
• Optimize the use of Visa’s Platforms & Solutions.
• Make a positive impact on Visa's Loyalty and Marketing team, fostering innovation and exploring new technologies such as Gen AI/ML.

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Qualifications

Basic Qualifications:

8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.

Preferred Qualifications:

9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD

8 plus years of relevant experience in distributed computing field.

Have prior experience in leading team of data engineers developing large scale ETL processing.

Have deep knowledge in technologies like Python, PySpark/Scala, Spark, Hadoop, Hive.

Have deep knowledge in backend application development using technologies like Python or Java or Kotlin or Scala.

Have extensive knowledge in data ware housing solutions.

Experience with AWS environment and services like S3, EMR, step functions, Glue etc.

Must have deep understanding in spark optimizations, optimizing resource sharing at cluster level.

Must have deep knowledge in any one of data cataloging tools.

Must have deep knowledge in real time streaming solutions and tools.

Must have deep knowledge in SDLC tools like Git/Jenkins/Jira.

Mush know UNIX scripting knowledge.

Expertise with AI/ML frameworks (TensorFlow, PyTorch, etc.), Java/J2EE, Spring, Spring Boot is plus

Experience in API Development using SOAP or REST, JSON, and XML is plus.

Have worked on ETL processing on large volumes of data and solved optimization problems will be plus.

Have worked in Feature engineering steps in ML life cycle is huge plus.

Have worked in PII data and handling with secure protocols is huge plus.

Strong experience in continuous delivery and DevOps, including infrastructure automation, monitoring, logging, and security implementation.

Proven knowledge of successful design, architecture, and development of complex systems.

Advanced understanding of AI/ML model development and deployment.

Ability to solve complex software development/design issues.

Demonstrated ability to deliver on multiple projects and manage priorities based on changing directions.