Senior Data Scientist

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.

Team Summary

As part of the Visa's Asia Pacific Consulting Practice, Visa Consulting and Analytics (VCA) applies deep expertise in payment industry to provide solutions and consulting services to assist clients with their key business priorities, drive growth and improve profitability. We drive tangible, impactful and financial results for Visa's clients, including card issuers, acquirers, and merchants. The VCA team provides a comprehensive range of consulting services to deliver solutions that address unique challenges in areas such as analytics, credit card product development, marketing, strategic growth, customer experience, digital payments, among others, and solves the most strategic problems for our clients.

What a Senior Data Scientist does at Visa:

The Senior Data Scientist is a key member of the Consulting and Analytics team. As a Senior Data Scientist you will be responsible for developing Data Analytics solutions to solve complex business problems. Here, you will be required to work with large data sets using quantitative techniques and build complex statistical models that learn from big data. We have a highly collaborative process and you are required to work across multiple teams and functions for developing cutting edge, creative and advanced analytic solutions and processes.

Key Responsibilities include:

• Directing the execution of medium to large analytic projects along with rest of the stakeholders in both internal and external

• Collaborating with the different teams to fully understand business requirements and desired business outcomes

• Defining detailed analytic scope and methodology, and creating analytic plan

• Executing on the analytic plan with appropriate data mining and analytic techniques

• Performing QA on data and deliverables by analysts and own deliverables

• Ensuring all project documentation is up to date and all projects are reviewed per analytic plan

• Ensuring project delivery within timelines and budget requirements

• Building on team's analytical skills and business knowledge

• Work as independent contributor mostly and as a team lead if needed by providing guidance to other team members where needed

• Enhancing existing analytic techniques by promoting new methodology and best practices in analytics field

• Providing subject matter expertise and quality assurance of complex data driven analytic projects

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Basic Qualifications

•5 or more years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Technical Qualifications:

•Hands on experience with one or more data analytics/programming tools such as SAS/Hadoop/R/SQL/Python/Hive

•Demonstrated expertise in designing, optimizing, and deploying Credit Risk Management models and Fraud Risk Control models

•Proficiency in some of the following statistical techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain Monte Carlo, Gibbs Sampling etc., Evolutionary Algorithms(e.g. Genetic Algorithms, Genetic Programming), Support Vector Machines, Neural Networks etc.

•Working knowledge in advanced data mining and modeling: Predictive modeling techniques (e.g., binomial and multinomial regression, ANOVA), Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis), Decision Tree techniques (e.g., CART, CHAID)

•Demonstrated experience in planning, organizing, and managing multiple analytic projects with diverse cross-functional stakeholders

•Demonstrated ability to innovate solutions to solve business problems

Business Qualifications:

•Results oriented with strong analytical and problem solving skills, with demonstrated intellectual and analytical rigor

•Good business acumen with strong ability to solve business problems through data driven quantitative methodologies. Experience in payment, retail banking, or retail merchant industries is preferred

•Understanding of Cards/Payments and Banking business model would be a plus

•Team oriented, collaborative, diplomatic, and flexible style, with the ability to tailor data driven results to various audience levels

•Detailed oriented, is expected to ensure highest level of quality/rigor in reports & data analysis

•Proven skills in translating analytics output to actionable recommendations, and delivery

•Experience in presenting ideas and analysis to stakeholders

•Exhibit intellectual curiosity and strive to continually learn

Preferred Qualifications

•Having already demonstrated a hands-on approach and the ability to earn the trust and respect of your team, you will bring a strong results orientation and exceptional organizational skills to the role. You will be passionate about delivering innovative analytics work, collaborating closely with colleagues to design impactful solutions, and driving projects from concept to execution. As a senior contributor, you will inspire your team through example, foster a culture of excellence, and ensure every initiative delivers measurable value to the organization.

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.