About Us
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
Job Description
Principal Responsibilities:
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Build long term relationship with large GCC clients, including client business and Data Science teams
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Manage full spectrum of VCA project journey, starting from sales, proposal building, pricing, project kickoff, execution, story building to post project implementation support
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Liaise with VCA leadership and participate in proposal approval meetings to get internal project approvals
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Develop and strengthen GCC Data Science risk capabilities and develop new risk solutions for the clients
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Responsible for developing analytics and model-based solutions for Visa’s issuer, acquirer, merchant, fintech clients addressing challenges such as market opportunity sizing, prospect targeting, cross sell/upsell, cross-channel marketing implementation, risk, fraud, and more general portfolio optimization programs
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With focus on building efficiency, find opportunities to automate the project pipeline of recurring projects using latest Data Science techniques
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Review, direct, guide, and inspire
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the analytical work of junior members in the team
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Identify innovation opportunities around data and data-related processes that will help our clients implement fact-based
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Work with regional and global Data Science teams to develop high-quality analytic products and solutions that promote Visa’s growth in the region
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Keep Visa at the forefront of technological advancement in Data Science by introducing cutting-edge tools and techniques for generating business insights
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Develop next-generation analytic methods where existing tools and techniques are inadequate to address business challenges
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Collaborate with internal Technology partners and Data Engineering function to best leverage Visa’s internal technology platforms, data, and the broader Visa ecosystem to support our clients’ technical data needs
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Manage workload for self and any direct reports, providing prioritization guidance for project flow to improve process efficiency
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Manage and grow talent within the team
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Develop, share, and build global best practices and knowledge management within the team
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Socialize innovative ideas and approaches that are scalable and have market demand
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Champion internal requirements around Model Risk Management, Visa Analytics Rules, and Global Privacy standards around client delivery to ensure that Visa’s highly regarded market standing is maintained
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Qualifications
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Minimum of 8+ years of expertise in applying Machine Learning solutions to business problems – model development and production experience required
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Post-graduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering
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Experience working in one or more of the Card & Payments markets around the globe, with specific responsibilities in payments, retail banking, or retail merchant industries
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Good understanding of Payments and the Banking industry, including card verticals such as consumer credit, consumer debit, prepaid, small business, commercial and co-branded product
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Expert knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies, with demonstrated ability to incorporate new techniques to solve business problems
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Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams, including resource planning and delivery implementation
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Experience in presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels
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Proven ability to deliver results within committed scope, timeline and budget
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Very strong people/project management skills and experience
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Ability to travel within GCC on short notice
Technical Expertise:
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Expertise in distributed computing environments / big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.)
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Familiarity with workings of Large Language models and ability to develop agents
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Capability to develop front end UI/UX would be plus
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Strong programming ability in different programming languages such as Python, Spark, R, Scala, Java, Matlab, C++, and SQL
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Experience in drafting solution architecture frameworks that rely on API’s and micro-services
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Familiarity with common data modeling approaches and ability to work with various datatypes including JSON, XML, etc.
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Ability to build data pipelines (e.g. ETL, data preparation, data aggregation and analysis) using tools such as NiFi, Sqoop, Ab Initio, familiarity with data lineage processes and schema management tools such as Avro
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Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain Monte Carlo, Gibbs Sampling, Evolutionary Algorithms (e.g. Genetic Algorithms, Genetic Programming), Support Vector Machines, Neural Networks, etc.
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Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial and multinomial regression, ANOVA), Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis), Decision Tree techniques (e.g., CART, CHAID)
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.
