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.
Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.
Job Description
Team Summary
To ensure that Visa’s payment technology is truly available to everyone, everywhere requires the success of our business partners such as financial institutions, merchants, fintechs, government agencies and internal business units. The Global Data Science group supports these partners by using our extraordinarily rich data set that spans more than 3 billion cards globally and captures more than 100 billion transactions in a single year.
Want more jobs like this?
Get jobs in Seoul, South Korea delivered to your inbox every week.
What a Director (Data Science) does at Visa:
- As the Director of Data Science, you will contribute to the Data Science teams in Korea and Mongolia, and be a part of Visa’s Global Data Science community.
- Take a leading role in Data Science projects and manage the team, providing support to both internal and external business partners in resolving business issues in various domains (e.g., digital, marketing, risk, etc.).
- Be involved in leading innovative works in Data Science and A.I. to enhance relevant capabilities.
- Provide technical leadership to the team that generates business insights based on big data, identifies actionable recommendations, and communicates the findings to the clients.
- Lead the team in discovering innovative ways to use our unique data to address business problems and provide relevant business insights.
- Spearhead communication with clients to understand their challenges and persuade them with data-driven solutions.
- Identify business opportunities to encourage the creation of new data solutions/products that are suitable for multiple clients.
- Lead collaboration with stakeholders across the team to identify business opportunities for leveraging Visa's data and data science approaches to drive Visa’s core business.
- Lead efforts to form data alliances with external parties who have beneficial data sources and capabilities to expand data-driven business.
- Lead in developing predictive/prescriptive models to increase and optimize customer experiences, revenue generation, data insights, risk management, and other business outputs.
- Support clients in exploring global business opportunities with their data solution and platform, leveraging Visa's global networks.
- Synthesize ideas/proposals in writing and engage in productive discussions with external or internal stakeholders.
- Provide guidance in advanced analytic techniques and business applications to unlock the value of Visa’s invaluable data set, in line with market trends, client needs, and emerging techniques.
- Perform as a team manager, focusing on people management to grow the market data science team and lead to apply agile framework.
Why this is important to Visa
As payments consulting arm of Visa, Data Science team is growing a team of highly specialized experts who can provide best-in-class payment expertise and data-driven strategies to clients. We are building a high-performing team of data scientists, data analysts and statisticians helping major organizations adapt and evolve to meet the changes taking place in technology, finance, and commerce, with cutting-edge, creative and advanced analytic solutions. The purpose of the team is to help both internal and external business partners grow their business and solve problems by providing advisory services through the use of data.
Projects you will be a part of:
- Data / Data Science Advisory
- VisaNet Data Analytic (Benchmarking / Market Landscape Analysis)
- Risk Management (Credit Scoring / Fraud Detection Model Development)
- Insight Monetization Engagement
- Data Platform / Product Commercialization (with external partners)
- Data Convergence / Partnership (3rd party data blending)
- Data Governance
- Data / A.I. Platform Development / Enhancement
- New Data Business Initiative
- Thought Leadership in Data Science (ex. Gen A.I. Application, A.I. Fairness, Sustainability Application)
Qualifications
• 12+ years of relevant work experience with a Bachelors Degree or 10+ years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 3+ years of work experience with a PhD
• Bachelors or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, Business Analytics, Industrial Engineering, or a related technical field
• Understanding the fundamentals of advanced M/L or D/L algorithms and Generative A.I.
• Experienced in extracting and aggregating data from large data sets using SQL/Hive or Spark
• Generating and visualizing data-based insights in software such as Tableau, Spotfire
• Deriving and communicating data-driven insights and conveying actionable recommendations
• Professional work in designing workplan and overall milestones to develop data solutions and bespoke data advisory project
• Capable to guide building predictive and descriptive models using cutting edge M/L , D/L and Gen A.I. (ex. LLM) tool kit, Jupyter notebooks, Python, PyTorch, TensorFlow, Langchain, LAMA2 etc.
• Previous exposure to financial services, credit cards or merchant analytics
• Managing analytics/data science projects from scoping to delivery, and engaging with internal/external stakeholders.
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.