Company Description
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.
Principle Responsibilities & Key Results Area
- Identify innovation opportunities around data and data-related processes that will help our clients implement fact-based decisioning processes within their cards and payments program.
- Work entails heavy focus on transaction data modelling and analytics for cards and payments products.
- Work with a broader team that consists of Business Managers, Consultants and Data Scientists from both Visa and client organizations to strategies, co-create, deploy, and reap the benefits of data-driven solutions.
- Work with regional and global Data Science teams to develop high-quality analytic products and solutions that promote Visa’s growth in the region.
- Focus on creating scalable framework for Gen AI, ML models.
- Keep Visa at the forefront of technological advancement in Data Science by introducing cutting-edge tools and techniques for generating business insights.
- Develop next-generation analytic methods where existing tools and techniques are inadequate to address business challenges.
- Drive commercialization of existing scalable assets (models, dashboards, solutions).
- 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.
- Develop, share, and build global best practices and knowledge management within the team.
- Socialize innovative ideas and approaches that are scalable and have market demand.
- 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.
- Work closely with Data Engineering, DS teams and vendors - communicate the business stakeholders needs and ensure the development team delivers within established acceptance criteria, including expected quality and performance.
- Drive strong collaboration with VCA CEMEA Service Line Leads (Portfolio Management, Digital, Risk, Merchant & Acquiring, Commercial) – understanding the market landscape and demand, identification of potential opportunities for scalable solutions, collecting business requirements and supporting in market enablement and Go-to-Market.
- Work with Global Practice Leads to incorporate best practice, source analytical or other services and leverage global consulting solutions.
- Deliver and manage a network of external Vendor or agency partners. Maintain excellent relationship with vendor team at-large, supervising deliveries as needed. Assist in selecting, recruiting, inducting and onboarding of vendors. Work with other teams and external consultants to develop new and improved tools and techniques for future Consulting activities.
- Manage the project budget and resources to perform all required duties.
- Liaise with VISA functional teams - Finance, Audit, Legal, Tax, Sourcing- to define and implement processes to optimize the daily engagement of vendors and the relationships with clients.
Qualifications
Key Competencies
- Minimum of 10+ years of expertise in applying Machine Learning solutions to business problems – model development and production experience required.
- Experience of using GenAI to solve business challenges.
- Post-graduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering.
- 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.
- 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.
- 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.
- Proven track record in commercializing analytical solutions.
- Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams, including resource planning and delivery implementation.
- Experience in presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels.
- Proven ability to deliver results within committed scope, timeline, and budget.
- Very strong people/project management skills and experience.
Technical Expertise
- Expertise in distributed computing environments / big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.).
- Familiarity with both common computing environments (e.g., Linux, Shell Scripting) and commonly used IDE’s (Jupyter Notebooks).
- Strong programming ability in different programming languages such as Python, R, Scala, and SQL.
- Experience in drafting solution architecture frameworks that rely on API’s and micro-services.
- 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.
- 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).
Leadership Competencies
- Demonstrates integrity, maturity, and a constructive approach to business challenges.
- Serves as a role model for the organization by implementing core Visa Values.
- Strives for excellence and extraordinary results.
- Uses sound insights and judgments to make informed decisions in line with business strategy and needs.
- Able to allocate tasks and resources across multiple lines of businesses and geographies.
- Able to influence senior management both within and outside Data Science.
- Successfully persuading internal stakeholders to commit to best-in-class solutions, when required.
- Leverages change management leadership as required.
- Fluency in English is mandatory.