Senior Manager, Data Science
Job details
Job DescriptionFor 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 ResponsibilitiesIdentify innovation opportunities around data and data related processes that will help our clients implement fact based decisioning processes within their cards and payments programWork 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 solutionsWork with regional and global Data Science teams to develop high quality analytic products and solutions that promote Visa's growth in the regionKeep Visa at the forefront of technological advancement in Data Science by introducing cutting edge tools and techniques for generating business insightsDevelop next generation analytic methods where existing tools and techniques are inadequate to address business challengesReview, direct, guide, and inspire the analytical work of junior members in the teamCollaborate 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 needsManage workload for self and any direct reports, providing prioritization guidance for project flow to improve process efficiencyManage and grow talent within the teamDevelop, share, and build global best practices and knowledge management within the teamSocialize innovative ideas and approaches that are scalable and have market demandChampion 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 maintainedLeadership CompetenciesDemonstrates integrity, maturity, and a constructive approach to business challengesServes as a role model for the organization by implementing core Visa ValuesShows respect for individuals at all levels in the workplaceStrives for excellence and extraordinary resultsUses sound insights and judgments to make informed decisions in line with business strategy and needsAble to allocate tasks and resources across multiple lines of businesses and geographiesAble to influence senior management both within and outside Data ScienceSuccessfully persuading internal stakeholders to commit to best-in-class solutions, when requiredLeverages change management leadership as requiredThis 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.Qualifications• 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 platformAdditional InformationVisa 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.
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