As a Senior Manager Data Science in the SSA Data Science team, this role serves as a strategic bridge between advanced analytics and business impact. The individual will lead the design and delivery of data driven solutions across cards and payments, influence client decision making, and grow high performing data science talent while advancing Visa analytics capabilities in the region.

Principal Responsibilities:
Data Driven Innovation and Client Impact:

• Identify and incubate data and analytics innovation opportunities that enable fact based decisioning across issuer and payments programs.
• Design predictive and prescriptive models using large scale transaction data to address client growth, risk, and portfolio performance challenges.
• Develop context driven prototypes, storyboards, and narratives that translate analytics into clear executive level insights.
• Socialize and scale analytics ideas with proven market demand and repeatability across SSA.

Advanced Analytics and Product Development:

• Lead analytics engagements with a strong focus on cards and payments transaction data modeling.
• Develop next generation analytical methods where existing tools and approaches are insufficient.
• Introduce and champion cutting edge data science techniques and tooling.
• Partner with regional and global Data Science teams to build high quality reusable analytic products.

Cross Functional and Client Collaboration:

• Work closely with Business Managers, Consultants, Data Scientists, and client stakeholders to co create, deploy, and operationalize analytics solutions.
• Collaborate with Technology and Data Engineering partners to leverage Visa platforms, data assets, and ecosystem capabilities.
• Support business development efforts including solution shaping and client discussions.

People Leadership and Talent Development:

• Review, guide, and inspire the analytical work of junior team members.
• Manage workload prioritization for self and direct reports to improve delivery efficiency.
• Coach, develop, and grow talent within the team.
• Build and share global best practices and contribute to analytics knowledge management.

Governance Risk and Standards:

• Champion Model Risk Management, Visa Analytics Rules, and Global Privacy standards
• Ensure analytics solutions are compliant, explainable, and aligned with Visa trust and risk principles.

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

Minimum of 10+ years of expertise in applying Machine Learning solutions to business problems. Model development and production experience required.
Post graduate degree or PhD in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering.
Experience working in one or more of the Card and Payments markets around the globe with specific responsibilities in payments, retail banking, or retail merchant industries.
Good understanding of Payments and the Banking industry, including card verticals such as consumer credit, consumer debit, prepaid, small business, commercial and co branded product.
Expert knowledge of data, market intelligence, business intelligence, and AI driven tools and technologies, with demonstrated ability to incorporate new techniques to solve business problems.
Experience planning, organizing, and managing multiple large projects with diverse cross functional teams, including resource planning and delivery implementation. Experience in presenting ideas and analysis to stakeholders whilst tailoring data driven results to various audience levels.
Proven ability to deliver results within committed scope, timeline, and budget.
Very strong people and project management skills and experience.

Technical Expertise:
Expertise in distributed computing environments and big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.)
Familiarity with common computing environments (e.g. Linux, Shell Scripting) and commonly used IDE’s (Jupyter Notebooks). Proficiency in SAS technologies and techniques.
Strong programming ability in different programming languages such as Python, R, Scala, Java, Matlab and SQL.
Experience in drafting solution architecture frameworks that rely on APIs and micro services
Proficient in techniques including Linear and Logistic Regression, Decision Trees, Random Forests, K Nearest Neighbors, Markov Chain Monte Carlo, Gibbs Sampling, Evolutionary Algorithms (e.g. Genetic Algorithms, Genetic Programming), Support Vector Machines, Neural Networks, etc.
Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g. binomial and multinomial regression, ANOVA), Classification techniques (e.g. Clustering, Principal Component Analysis, factor analysis), Decision Tree techniques (e.g. CART, CHAID)

Leadership Competencies:
Demonstrates integrity, maturity, and a constructive approach to business challenges.
Serves as a role model for the organization by implementing core Visa Values.
Shows respect for individuals at all levels in the workplace.
Strives for excellence and extraordinary results.
Uses sound insights and judgments to make informed decisions in line with business strategy and needs.
Able to allocate tasks and resources across multiple lines of business and geographies.
Able to influence senior management both within and outside Data Science.
Successfully persuades internal stakeholders to commit to best in class solutions when required
Leverages change management leadership as required.

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.