Employer Active
Job Alert
You will be updated with latest job alerts via emailJob Alert
You will be updated with latest job alerts via emailPrinciple Responsibilities & Key Results Area
Maintain excellent relationship with vendor team atlarge 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.
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 cobranded product
Expert knowledge of data market intelligence business intelligence and AIdriven 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 crossfunctional teams including resource planning and delivery implementation Experience in presenting ideas and analysis to stakeholders whilst tailoring datadriven 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 KNearest 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 bestinclass 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 :
Fulltime
Full-time