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.
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Job Description Leading, executing, and delivering data science projects for one of Visa's key bank clients in Malaysia.Hands on develop detailed project scopes and methodologies, designing, and implementing solutions using appropriate tools and techniques.Maintaining quality control and up-to-date documentation for all data science projects.Innovating by utilizing Visa's data and client data to meet client needs.Enhancing existing data science and analytic techniques by promoting new methodologies and best practices.Fostering thought leadership in the data science domain and building intellectual property through innovation.Managing communication with clients and stakeholders effectively.Mentoring, guiding, and supervising data scientists in the project team.Delivering analytics projects from inception to completion, providing actionable insights and recommendations.Identifying opportunities for innovation using non-traditional data and new modeling techniques.Managing internal and external stakeholders.Building data science visualization capabilities to address client problems.Advocating for data science within partner organizations, advising and coaching analytical teams, and sharing best practices and case studies.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.
Qualifications Degree (master's or Ph.D. would be an advantage) in Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering or equivalent experience.7+ years of experience in performing data exploration and feature engineering.10 years of professional work experience in banking, payments, or related industryHands on experience with data analytics/programming tools such as SAS/Salford SPM/Hadoop/R/SQL/Python/Hive, and a working knowledge of Hadoop ecosystemProficiency in statistical techniques: Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc.Demonstrated experience in planning, organizing, and managing multiple and concurrent analytics projects with diverse cross-functional stakeholders.Strong internal team and external client stakeholder management with a collaborative, diplomatic, and flexible style, able to work effectively in a matrixed organization.Excellent presentation and storytelling skills, including strong oral and written capabilities.Storyboarding and data storytelling including strong Excel and PowerPoint skills.In market experience and/or knowledge of local language, culture as well as industry regulations Additional Information All your information will be kept confidential according to EEO guidelines.