Manager, Data Science-2

  • Full-time
  • Job Family Group: Product and Design

Company Description

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world.

Progress starts with you.

Job Description

Job Description:
Visa Consulting and Analytics (VCA) is the consulting arm of Visa, and drives tangible, impactful results for clients. Drawing on our expertise in consulting, data analytics, technology, payments and economics, VCA solves the most strategic problems for our clients. VCA's core client segments include issuers, acquirers, merchants, fintechs, payment enablers and governments. 

The Intelligence & Data Solutions (IDS) team at VCA consists of data scientists, analysts, and engineers who provide analytics solutions. Their goal is to leverage VisaNet, one of the largest datasets globally, to help clients enhance their performance and increase profitability. 

What a Data Scientist, VCA does at Visa:
We are looking for a Data Scientist to join our VCA team in Malaysia. This role requires transforming raw data into actionable insights that drive business strategies, improve execution and performance of the full cardholder lifecycle. 

The ideal candidate will work closely with Visa’s clients to gather and manage project inputs, analyze data to form conclusions and recommendations, execute and analyze results to improve outcomes. 

Key Responsibilities:

  • Lead, execute, and deliver data science projects for Visa's key clients. 
  • Develop project scopes, methodologies, and implement solutions using appropriate tools. 
  • Understand the Client’s current initiatives and priorities and align with key stakeholders.
  • Manage and deliver analytics projects from conception to completion with actionable insights and recommendations. 
  • Gather and analyze data from VisaNet (i.e., Visa’s transaction data), client’s owned data and 3rd party data sources to understand customer behavior, preferences and trends to help business develop business strategies, optimization activities and improvement of products, marketing techniques. 
  • Maintain quality control and documentation for projects. 
  • Innovate with Visa's and client data to meet needs. 
  • Clearly communicate the findings and recommendations from analysis, drive deployment and implementation of analytics solutions, and track business value impact. 
  • Independently develop and articulate a compelling storyline with clear insights and actionable recommendations for clients. 
  • Actively seek out opportunities to innovate by using non-traditional data and new modelling techniques fit for purpose to the needs of our clients. 
  • Structure documents and project deliverables leveraging data insights and client inputs. 
  • Foster thought leadership and innovation in data science. 
  • Manage communication with clients and stakeholders. 
  • Identify opportunities for innovation using new techniques. 
  • Build visualization capabilities to address client problems. 
  • Identify market trends through deep analysis of payment industry information. 
  • Manage the transfer of technical knowledge for business solution implementation. 

Client Management: 

  • Manage and take ownership of all data-related client deliverables and discussions 
  • Navigating complex team dynamics 
  • Work independently, seeking guidance as needed while ensuring ownership 
  • Influence multiple teams they work with or lead

*This is a hybrid position, expectation of days in the office will be confirmed by your Hiring Manager. 

Qualifications

Qualifications:

  • Bachelor’s degree with 5–8+ years of relevant work experience in data analytics, data science, or a related field.
  • Hands-on experience applying data analytics and predictive modeling to solve business problems, ideally within the banking, payments, or adjacent sectors.
  • Advanced proficiency in SQL, with the ability to write complex queries for data extraction, transformation, and manipulation.
  • Strong capability in handling and processing large-scale datasets efficiently.
  • Exposure to big data tools such as Apache Hive and Spark will be considered a plus.
  • Proficiency in Python and relevant analytics/modeling libraries, including Pandas, NumPy, scikit-learn, and TensorFlow/Keras/PyTorch.
  • Sound understanding of statistical techniques, exploratory data analysis, and data visualization best practices.
  • Practical experience with machine learning algorithms, including supervised learning models such as Linear/Logistic Regression, Random Forest, and Gradient Boosting, as well as clustering techniques such as K-Means and GMM.
  • Familiarity with neural networks and deep learning models.
  • Demonstrated experience in building, tuning, and evaluating machine learning models using scikit-learn.
  • Knowledge of the payments ecosystem, retail banking landscape, risk analytics, and regulatory environment in Malaysia is strongly preferred.
  • Strong project management and stakeholder management skills, with the ability to manage multiple priorities concurrently.
  • Collaborative, adaptable, and comfortable working in a cross-functional, matrixed environment.
  • Strong presentation, verbal, and written communication skills, with the ability to translate complex technical findings into clear business insights.

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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