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Company Description

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

Join Visa: A Network Working for Everyone.


Job Description

As the Data Science Lead for Visa Consulting & Analytics in Thailand, your key responsibilities include:

  • Leading, executing, and delivering data science projects for clients in Thailand.
  • Developing detailed project scopes and methodologies, designing, and implementing solutions using appropriate tools and techniques.
  • Building strong relationships with Visa partners, clients, and corresponding data science & analytics teams, driving collaboration, and ensuring the implementation of Visa's recommendations.
  • Maintaining quality control and up-to-date documentation for all data science projects.
  • Innovating by utilizing Visa's data, client data, and non-traditional data sources 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.
  • Supervising data scientists reporting to this role.
  • Developing data-driven solutions using Visa data.
  • Building data science visualization capabilities to address client problems.
  • Driving innovation using data science techniques.
  • Advocating for data science within partner organizations, advising and coaching analytical teams, and sharing best practices and case studies.
  • Continually assessing the environment to challenge assumptions about data sources, potential analytics partners, tools, talent, and infrastructure.
  • Exploring and adopting leading methodologies and best practices from other international markets

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

We are looking for a motivated, analytical minded individual with a track record of using data science and analytics expertise to unlock business value. A successful candidate should have accumulated a variety of industry experience, be curious about payments industry and application of data analytics, should be results-driven and client-centric.
  • 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

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.

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āļˆāļģāļ™āļ§āļ™āļžāļ™āļąāļāļ‡āļēāļ™:n/a
āļ›āļĢāļ°āđ€āļ āļ—āļšāļĢāļīāļĐāļąāļ—:āļāļēāļĢāđ€āļ‡āļīāļ™āđāļĨāļ°āļāļēāļĢāļ˜āļ™āļēāļ„āļēāļĢ
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A certain excitement comes with working at one of the world’s most recognized and most respected companies. At Visa, we work to power the global economy by extending the power of electronic payments to people, businesses and governments everywhere in the world Visa’s innovations enable its bank c ... āļ­āđˆāļēāļ™āļ•āđˆāļ­

āļĢāđˆāļ§āļĄāļ‡āļēāļ™āļāļąāļšāđ€āļĢāļē: Common Purpose, Uncommon Opportunity. Everyone at Visa works with one goal in mind – making sure that Visa is the best way to pay and be paid, for everyone everywhere. This is our global vision and the common purpose that unites the entire Visa team. As a global payments technology company, tech is ... āļ­āđˆāļēāļ™āļ•āđˆāļ­

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