Principle Responsibilities & Key Results Area
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Qualifications :
Key Competencies
Minimum of 10 years of expertise in applying Machine Learning solutions to business problems, model development, and production experience required.
Postgraduate 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 products.
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 IDEs (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 APIs and microservices.
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.
Additional Information :
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.
Remote Work :
No
Employment Type :
Full-time