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.
For Senior Manager of Data Science role in the GCC Data Science team, we are seeking an innovative and analytical thinker to champion our data driven strategies within the region. As a Data Science Senior Manager, you will participate in business development, build predictive and prescriptive models, and develop context based prototypes and high impact storyboards that promote data driven strategies and solutions for Visa clients. This role is dedicated exclusively to working for on a key client account based in the Qatar market.
Principal Responsibilities
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 Senior Managers, Consultants and Data Scientists from both Visa and client organizations to strategize, 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
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
Review, direct, guide, and inspire the analytical work of junior members in the team
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
Manage workload for self and any direct reports, providing prioritization guidance for project flow to improve process efficiency
Manage and grow talent within the team
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
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
Shows respect for individuals at all levels in the workplace
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
This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
• Minimum of 10+ years of expertise in applying Machine Learning solutions to business problems, model development and production experience required
• 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
• 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
• 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), proficiency in SAS technologies and techniques
• Strong programming ability in different programming languages such as Python, R, Scala, Java, Matlab, C++, 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)
Hands on experience on Cloudera Data Platform and AWS ML platform
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.