Data Scientist (CEMEA)

  • Dubai - United Arab Emirates
  • Full-time

Company Description

As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable and secure payment network - enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company's dedication to innovation drives the rapid growth of connected commerce on any device, and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.

At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.

You're an Individual. We're the team for you. Together, let's transform the way the world pays.

 

Job Description

We are seeking an innovative and analytical thinker to support our Regional Marketing and Digital Analytics delivery team. As a Data Scientist, you will be responsible for developing marketing analytics solutions for Visa’s Issuer and Merchant clients. Your models will address challenges such as market opportunity sizing, prospect targeting, cross sell/upsell, cross channel marketing measurement and return on marketing investment (ROMI) programs. You will be directly responsible for devising programs that solve for campaign execution and tracking, measuring the impact of digital and social experience on consumer behavior, and sizing internal and external factors that influence marketing and brand health.

 

Principal Responsibilities

  • Develop marketing analytics components, including prospect targeting, cross sell/upsell programs for domestic and cross-border transaction behavior, and attrition risk
  • Provide expertise around marketing measurement techniques (e.g., A/B testing and test/control design), brand and advertisement tracking, return on marketing investment (ROMI), impact across multiple cross-channel marketing activities, and optimization of marketing investment allocation
  • Leverage expertise in estimating the impact of social and digital experiences on sales and brand
  • Design, build, and manage contextual, real-time marketing programs
  • Drive integration with next-generation technologies that infer how customers’ feelings, tastes and preferences (psychographics) can influence point-of-purchase strategy, product development and placement, brand positioning, etc.
  • Identify potential opportunities based on changes in broader ecosystem, such as advances in methodologies used for marketing targeting, attribution and measurement; legislative or economic changes; evolving consumer needs; evolution of the competitive landscape; emerging partnership opportunities; etc.
  • Identify creative ways to combine Visa’s internal data with Visa’s sponsored consumer insights surveys and data from external competitive intelligence systems ( e.g., Euromonitor and Data Monitor) to produce actionable insights for marketing initiatives
  • Perform quality assurance on data and deliverables by analysts; ensure high quality of delivery on own deliverables
  • Ensure that project delivery is within timelines and budget requirements
  • Build on team’s analytical skills and business knowledge
  • Provide subject matter expertise and quality assurance of complex data-driven analytic projects

Qualifications

Professional Experience

  • Minimum of  6+ 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, 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

  • Experience 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 micro-services
  • 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)
  • Delivery of results within committed scope, timeline and budget
  • Very strong people/project management skills and experience
  • Ability to travel within CEMEA on short notice

 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

Leadership Competencies

  • Demonstrates integrity, maturity and a constructive approach to business challenges
  • Role model for the organization and implementing core Visa Values
  • Maintains respect for individuals at all levels in the workplace
  • Continuously strives for excellence and extraordinary results
  • Uses 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
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