Head of Data Science, SSA at Visa

Job Description

Position Summary

• The Senior Director of Data Science would be leading Data Science for the SSA (SSA) team.  We are seeking an innovative and analytical thinker to champion our data-driven strategies for the region. As a Senior Director, you are expected to participate in business development, guide team to develop predictive and prescriptive models, develop context-based proto-types and high impact storyboards to promote a data-driven strategy and solutioning approach for the company. The candidate should be aware of & comfortable in using new technologies such as Agentic AI & Gen AI.

Principal Responsibilities

• Manage and execute projects and client engagement for all the clients in SSA for VCA
• Leverage learnings from other region and apply those in SSA
• Provide leadership and mentoring to junior resources within SSA DS team
• Establish and maintain relationship with key stakeholders in SSA market
• Work closely with Hub DS team to leverage data solutions & consumer signals to create efficiency within the region.
• Use strong banking knowledge to design and develop campaign processes for the clients
• 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
• 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
• Managing team workload, providing prioritization guidance for project flow to improve process efficiency
• Manage and grow talent within the team
• Develop, share, and build global best practices and knowledge management within the team
• Socialise innovative ideas and approaches that are scalable and have market demand

Qualifications

Professional Experience

• Minimum of 15+ years of analytics expertise in applying statistical solutions to business problems
• Experience working in one or more of the Card Payments markets around the globe
• Post-graduate degree (Masters or PhD) in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent
• 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 planning, organising, and managing multiple large projects with diverse cross-functional teams
• Demonstrated ability to incorporate new techniques to solve business problems

Technical Expertise

• Expertise in distributed computing environments / 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); proficiency in SAS technologies and techniques
• Strong programming ability in different programming languages such as Python, R, Scala, Java, Matlab, C++, 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, 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)
• Deliver results within committed scope, timeline and budget

Business Experience

• 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/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
• Very strong people/project management skills and experience
• Ability to travel within short notice