Manager, Data Science at Visa

Job Description

• The Senior Data Scientist is a Manager level role in the Sub-Saharan Africa (SSA) team and positioned within the Visa Consulting & Analytics (VCA) business unit. VCA primarily provides data driven consulting services to Visa clients globally.  We are seeking an innovative and analytical thinker to execute on our data-driven strategies for the SSA sub-region. As a Senior Data Scientist, you are expected to participate in business development, develop descriptive analytics, predictive and prescriptive models and develop context-based proto-types and high impact storyboards to promote a data-driven strategy and solutioning approach for the company and our clients. The role does not currently have any direct reports or line management responsibility.

Principal Responsibilities

• Conducting transactional data analysis and developing advanced statistical models within our distributed computing environment using big data technologies for internal and external clients and stakeholders.
• Identify strategic and tactical innovation opportunities around data and data-related processes that will promote fact-based decisioning processes and scalable solutions.
• Execute and support the strategic direction and the 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
• Contribute to keeping us at the forefront of technical advancement in Data Science by using cutting-edge tools and techniques for generating business insights
• Develop next-generation analytic methods where existing techniques are not adequate to address business challenges
• Collaborate with technology partners to build an Analytics Technology Ecosystem that supports advanced modelling and decisioning.
• Develop, share, and build global best practices and knowledge management within the team
• Socialize innovative new ideas and approaches that are scalable and have market demand
• Communicate effectively to technical and non-technical audiences including developing and delivering effective client presentations.

Qualifications

• Minimum of 5+ years of analytics expertise in applying statistical solutions to business problems
• Post-graduate degree (Masters or PhD would be an advantage) in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent.

Professional Experience

• Experience working in one or more of the Card Payments markets around the globe is an advantage
• Good understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchants.
• Good knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies
• Experience planning, organizing, and executing multiple 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 / 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
• Familiarity with 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
• Very strong project management skills and experience

Business Experience

• Results-oriented with strong problem solving skills and demonstrated intellectual and analytical rigor
• Good business acumen with a trackrecord 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

Leadership Competencies

• Demonstrates integrity, maturity and a constructive approach to business challenges
• Role model for the organization in showcasing 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/influence internal stakeholders for building best-in-class solutions
• Change management leadership