Director, Data Engineering and Machine Learning Operations, Visa Predictive Models

Company Description

Visa is a global leader in digital payment transactions, facilitating over 215 billion payment transactions between consumers, merchants, financial institutions, and governmental entities across over 200 countries and territories each year. Our goal is to connect the world through the most innovative, convenient, reliable, and secure payment network, thus empowering individuals, businesses, and economies to prosper.

By joining Visa, you are becoming a part of a culture of purpose and belonging – a place where your growth is prioritized, your identity is valued, and the work you do matters. We believe an economy that includes everyone, everywhere lifts everyone, everywhere. Your work will significantly influence billions of people globally – assisting in providing financial access for the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

Team Summary

The Risk and Identity Solutions (RaIS) team delivers risk management services for banks, merchants, and other payment networks. Real-time insights for risk management, generated through machine learning and AI models, constitute the backbone of many of these services. Developed by Visa Predictive Models (VPM) team, the continuous refinement and efficient deployment of these models is critical to our future success. To support our fast-expanding array of predictive models, we are in the search for data engineers who have a passion for managing high volumes of data, streamlining processes, and standardizing tools.

Job Description:

In this role, within the VPM team, you will contribute significantly to the development of RaIS fraud prevention solutions. You will be tasked with developing a global engineering team focused on the development of data assets, standardized tools, and critical data pipelines.

You will collaborate closely with global stakeholders in VPM Product, VPM Data Science, Visa Research, and Visa technology teams to identify team requirements and outline a strategic roadmap. Subsequently, you will apply your strategic planning and your technical understanding of data engineering, tools, and data architecture, to design and create the solutions outlined in our roadmap.

You must be a hands-on expert with the ability to guide both data engineering and data science teams in crafting effective data engineering solutions. Furthermore, you should possess a knack for recruitment and demonstrated ability in leading and developing engineering teams.

The position is based at Visa's offices in Bangalore, India.

Essential functions:

• Recruit and nurture a team of skilled engineers capable of staying current with and leading in this field.
• Create efficient and robust Spark pipelines to generate the data sets required for reporting, data marts, and predictive modeling.
• Develop, implement, and enable processes for feature engineering, data operations, and deployment monitoring.
• Construct and maintain high-performing ETL processes to create and uphold feature stores to facilitate predictive modeling.
• Help with the creation and deployment of enterprise-grade scoring code, as necessary.
• Develop processes to review deployment pipelines, build test cases, monitor, alert, and maintain relevant documentation.
• Collaborate with Data Science teams to develop efficient and configurable model refit pipelines to expedite model development and deployment.
• Cultivate relationships and foster collaboration with various Technology teams to provide and acquire feedback, aiming to enhance MLOps.
• Define and create technical/data documentation and experience with code version control systems (e.g., git). Ensure the accuracy, integrity, and consistency of data.

This position is hybrid. Hybrid employees have the option to divide their time between remote and in-office work. Individuals in hybrid roles are expected to work from the office for 2-3 designated days each week (as decided by leadership/site), with a general expectation of being in the office 50% or more of the time, subject to business necessities.

Qualifications

Basic Qualifications
• 12+ years of work experience with a Bachelor’s Degree or 10+ years of work experience with a Master's or Advanced Degree in an analytical field such as computer science, statistics, finance, economics, or a relevant area.
• Practical knowledge of the Hadoop ecosystem and related technologies (e.g. HDFS, MapReduce, YARN, Spark, Kafka, MLlib, GraphX, iPython, sci-kit, Pandas etc.)

Preferred Qualifications:
• 12+ years of relevant work experience with a Master's or Advanced Degree specializing in Computer Science, Information Science, Statistics, Data Engineering and Analytics, or a relevant field.
• Significant experience working with global teams and Fortune 500 companies spearheading large-scale implementations of data warehouses and data engineering solutions.
• Hands-on experience dealing with large-scale data ingestion, processing, and storage within the Hadoop ecosystem.
• Experience managing teams implementing ETL pipelines in Spark, Python, Scala, HIVE, or Kafka to process transactional and account-level data.
• Experience dealing with complex, high-volume, multi-dimensional data and machine learning models based on unstructured, structured, and streaming datasets.
• Familiarity with scheduling tools (Airflow, Control-M) and creating data processing orchestration workflows.
• A profound understanding of the development and implementation aspects of ML/AI, especially dealing with billion-scale datasets. Ability to accept small-scale developed models and implement them with necessary configuration and customization, while upholding model performance.
• Demonstrated leadership ability to understand and leverage available technology while offering recommendations and insights into improvement opportunities.
• Deep understanding of MLOps processes, including the ability to build and integrate the code within the established CI/CD framework.
• Experience creating/supporting production software/systems and a demonstrated track record of identifying and resolving performance issues for production systems.
• Strong written, spoken, and interpersonal skills necessary to effectively communicate technical insights and recommendations to business customers and the leadership team.
• Experience working with technology and business teams on Data Governance, Data Quality, and Data Architecture initiatives.

Additional Information

Visa is an Equal Opportunity Employer. All qualified candidates will receive consideration for employment without discrimination on the basis of race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status. Visa will also consider for employment qualified candidates with criminal histories in a manner consistent with EEOC guidelines and relevant local law.