Head of Data Science, SSA, Visa

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 IDEs (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 APIs 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

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.

Remote Work :

No

Employment Type :

Full-time