To ensure that Visa’s payment technology is truly available to everyone, everywhere requires the success of our ecosystem of key banks, merchants, fintechs and Governments. 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. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. To support our rapidly growing group, we are looking for Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to tackle meaningful business problems.

We are seeking an innovative and analytical thinker to support our Data Science team in CISSEE within Visa Consulting & Analytics. As a Director: Data Scientist, you will be responsible for developing analytics and model-based solutions for Visa’s issuer, acquirer, merchant, fintech and Government clients. Your models will address challenges such as market opportunity sizing, prospect targeting, cross sell or upsell, cross-channel marketing implementation, risk, fraud, and more general portfolio optimization programs. You will be directly responsible for a limited number of ad-hoc reporting activities to accompany the main work of delivering descriptive, predictive, and prescriptive analytical projects, applying appropriate analytic methodologies and techniques to solve client’s business objectives. This role’s primary function is to support external clients, with some exposure to internal clients’ projects.

Global Data Science is the engine of analytics at Visa this is a high-performing team of Data Scientists, Data Analysts, Statisticians, and Business Analysts from a variety of countries – serving the Central Europe, Middle East and Africa (CEMEA) geographies. The Director of Data Science is a lead Data Scientist role in the Sub-Saharan Africa (SSA) Visa Consulting & Analytics team.  As a Director, you will be accountable for leading the design, development and implementation of analytics-driven strategies and solutions. In this role, you will partner with Visa Consulting & Analytics, Business Development, Product, Finance and Technology teams across the organization to implement solutions that drive business performance.

Responsibilities:

Principal Responsibilities:

• Provide leadership to identify strategic and tactical innovation opportunities around data and data-related processes that will promote fact-based decisioning processes
• Help set strategic direction and roadmap for the Data Science group in Sub-Saharan Africa
• Manage and execute projects and client engagement for the large projects in CISSEE
• Provide leadership and mentoring to junior resources who are currently involved in the project
• Provide leadership to identify strategic and tactical innovation opportunities around data and data-related processes that will promote fact-based decisioning processes
• Help set strategic direction and the roadmap for the Data Science group in CISSEE
• Work with regional and global Data Science teams to develop high-quality analytic products and solutions that promote growth and business development for the region
• Keep us at the forefront of technical advancement in Data Science by introducing cutting-edge tools and techniques for generating business insights
• Develop next-generation analytic methods where existing techniques are not adequate to address business challenges
• Review, direct, guide, and inspire the analytical work of junior members in the team
• Collaborate with technology partners to build an Analytics Technology Ecosystem that supports advanced decisioning
• Develop, share, and build global best practices and knowledge management within the team
• Socialise innovative new ideas and approaches that are scalable and have market demand

Leadership Competencies:

• Demonstrates integrity, maturity and a constructive approach to business challenges
• Role model for the organization and implementing core Visa Values
• Respect for the Individuals at all levels in the workplace
• Strive for Excellence and extraordinary results
• Use sound insights and judgments to make informed decisions in line with business strategy and needs
• Leadership skills include an ability to allocate tasks and resources across multiple lines of businesses and geographies. Leadership extends to ability to influence senior management within and outside Analytics groups
• Ability to successfully persuade or influence internal stakeholders for building best-in-class solutions
• Change management leadership

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

• Results-oriented with strong problem-solving skills and demonstrated intellectual and analytical rigor
• Good business acumen with a track record in solving business problems through data-driven quantitative methodologies. Experience in payment, retail banking, or retail merchant industries is preferred
• Team oriented, collaborative, diplomatic, and flexible style
• Very detailed oriented, is expected to ensure highest level of quality or rigor in reports and data analysis
• Proven skills in translating analytics output to actionable recommendations and delivery
• Experience in presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels
• Exhibits intellectual curiosity and a desire for continuous learning
• Experience working in one or more of the Payments markets around the globe preferred
• Good understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchant
• Good knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies
• Experience building and cultivating teams
• Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams
• Demonstrated ability to incorporate new techniques to solve business problems
• Demonstrated resource planning and delivery skills

Technical Expertise:

• Expertise in distributed computing environments or big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.)
• Ability to write scratch MapReduce jobs and fluency with Spark frameworks
• Familiarity with both common computing environments (e.g. Linux, Shell Scripting) and commonly-used IDE’s (Jupyter Notebooks)
• Strong programming ability in different programming languages such as Python and SQL
• Experience in drafting solution architecture frameworks that rely on API’s and microservices
• Familiarity with common data modeling approaches, and ability to work with various datatypes including JSON, XML, etc.
• Ability to build data pipelines (e.g. ETL, data preparation, data aggregation and analysis) using tools such as NiFi, Sqoop, Ab Initio familiarity with data lineage processes and schema management tools such as Avro
• Proficient in some or all of the following techniques: Linear & 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. Strong understanding in data architecture, LLM, and Gen AI concepts.
• 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)
• Deliver results within committed scope, timeline and budget
• Very strong people or project management skills and experience

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.