Job Specifications
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.
Job Description
With data being the fuel that drives our future - our strategies, policies, and business successes around data will define our future growth prospects. Unlocking the value available through the innovative use of data on behalf of consumers, businesses, and communities is key to our future. With our ongoing commitment to Visa’s Data Values and the responsible use of data, we at Visa have a bold vision to continue to grow and accelerate our data-related businesses and capabilities.
Led by Visa’s Chief Data Officer, the Global Data Office coordinates high-impact, complex, company-wide projects related to data business strategy, critical investments, policy development, and marketplace execution. Working closely with Visa’s Chief Privacy Officer, the Technology organization, the wider data community, and the full set of Visa’s global lines of business, the Global Data Office is evolving Visa’s data-related work with momentum and enthusiasm. Driven by its commitment to trusted use of data, Visa is seeking enthusiastic leaders who are change-agents and passionate about the future of data around the world.
The AI/ML Products & Analytics team is creating the next generation of scalable and responsible AI, ML and Data Innovations and products to solve client and consumer problems. We are a cross-functional team of data scientists, product managers, AI and data engineers, program managers focused on generating value for the payments ecosystem.
Responsible for building end to end automated pipeline for AI/ML models including model development, model validation, model refit, model recalibration, model monitoring and model serving etc.
Work collaboratively with Data Scientists, Data Engineer, Software Engineers, Product Manager and cross-functional partners to design and deploy AI/ML based solutions and products
Lead end to-end deployment and maintenance of machine learning models in production, from concept, design, implementation, to rollout, ensuring the highest quality and performance
Stay updated on state-of-the-art algorithmic techniques and recognize promising innovations, adapting them to Visa’s unique business and offerings.
Design, implement, and maintain reliable, high-performance distributed systems.
This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.
Relocation assistance is not provided for this role.
Qualifications
Basic Qualifications:
2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
Preferred Qualifications:
3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
Master’s or Advanced Degree in a Quantitative field such as Statistics, Computer Science, Economics, Engineering, or equivalent with analytics expertise in applying statistical solutions to business problems
3+ years of relevant experience in AI/ML model development and deployment with an Advanced Degree
Experienced with building AI/ML model pipelines and creating robust and scalable AI/ML solutions.
Advanced programming ability building Machine learning pipelines in Spark, Python, HIVE or Scala, Airflow, github, MLflow that deploy AI models into production
Exposure to model management and governance practices. Ability to take decisions around model drift to monitor and refine models continuously.
Working knowledge of Hadoop ecosystem and associated technologies, (For e.g. Apache Spark,
MLlib, GraphX, iPython, sci-kit, Pandas etc.)
Proficient in advanced data mining and statistical modeling techniques, including Predictive
modeling (e.g., binomial and multinomial regression), Classification techniques (e.g.,
Clustering, Principal Component Analysis, factor analysis), Decision Tree, Transformer model, and LLM etc
Experience working with large scale data ingestion, processing and storage in distributed
computing environments / big data platforms (Hadoop) as well as common database systems and value stores (Parquet, Avro, HBase, etc.).
Familiarity with both common computing environments (e.g., Linux, Shell Scripting) and commonly used IDE’s (Jupiter Notebooks).
Experience working with AWS for MLOps model development and model implementation is preferred but not required.
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