- 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.
- 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 industry
- Hands on experience with data analytics/programming tools such as SAS/Salford SPM/Hadoop/R/SQL/Python/Hive, and a working knowledge of Hadoop ecosystem
- Proficiency 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
All your information will be kept confidential according to EEO guidelines.
