Data Modeler / ETL Developer, Central Europe, Middle East and Africa (CEMEA) Data Science, Visa - Manager

  • Bengaluru, Karnataka, India
  • Full-time

Company Description

Common Purpose, Uncommon Opportunity.  Everyone at Visa works with one goal in mind – making sure that Visa is the best way to pay and be paid, for everyone everywhere. This is our global vision and the common purpose that unites the entire Visa team.  As a global payments technology company, tech is at the heart of what we do: Our VisaNet network processes over 13,000 transactions per second for people and businesses around the world, enabling them to use digital currency instead of cash and checks. We are also global advocates for financial inclusion, working with partners around the world to help those who lack access to financial services join the global economy. Visa’s sponsorships, including the Olympics and FIFA™ World Cup, celebrate teamwork, diversity, and excellence throughout the world. If you have a passion to make a difference in the lives of people around the world, Visa offers an uncommon opportunity to build a strong, thriving career. Visa is fueled by our team of talented employees who continuously raise the bar on delivering the convenience and security of digital currency to people all over the world. Join our team and find out how Visa is everywhere you want to be.

Job Description

Position Summary

We are seeking an innovative and analytical thinker to work with our Data Science and Consulting teams in the Central Europe, Middle East and Africa (CEMEA) region. The Data Modeler / ETL Developer is expected to deliver prepped and cleansed data from source systems into analytical environments for modeling and development purposes. The role promotes a data-driven solutions approach for Visa’s clients (internal and external) by ensuring that consistent sources of certified data are available throughout the organization. Visa’s own data assets will be supplemented with client and other third-party sources for ingestion and provisioning as required.

Principal Responsibilities

  1. Serve as an analytics expert in designing, developing and implementing best-in-class data pipelines and ETL methodologies to support business needs.
  2. Support the internal data community by investigating and mapping available data sources.
  3. Manage internal catalogue of certified data feeds for use by end data consumers.
  4. Collaborate with internal and external partners to fully understand business requirements and desired business outcomes.
  5. Demonstrate execution proficiency in handing multiple medium-to-large analytics projects in a teaming environment that includes the rest of the Data Science and Consulting team.
  6. Draft detailed scope for assigned projects, addressing suggested methodology, analytics and development plan. Ensure all project documentation is up to date and all projects are reviewed per analytics and development plan.
  7. Execute on the analytics and development plan with appropriate data mining and analytical techniques.
  8. Perform quality assurance of data and deliverables for work performed by other Data Scientists and self, including adherence to Visa’s Model Risk Management policies.
  9. Ensure project delivery within timelines and budget requirements.
  10. Build on team’s analytical skills and business knowledge.
  11. Enhance existing analytics techniques by promoting new methodologies and best practices in the data management field.
  12. Provide subject matter expertise and quality assurance of complex data-driven analytic projects.


Professional Experience


·       Minimum of 6+ years of data modeling and analysis expertise in developing ETL pipelines (extract, transform, and load) for business outcomes.

·       Excellent knowledge, experience and understanding of quantitative techniques (modelling, statistics, root-cause analysis, etc.) with a focus on Card and Payments.

·       Good understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchant portfolios.

·       Experience working in one or more of the Card and Payments markets around the globe.

·       Familiarity in working with big data, both structured and unstructured, on a shared distributed computing environment.

·       Proven ability to develop high-quality, production-ready data feeds for business consumption.

·       Working knowledge of code optimization best practices for run-time performance.

·       Post-graduate degree (Masters or PhD) in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent.

·       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 solution architecture frameworks that rely on API’s and micro-services.
  • Familiarity with common data modeling approaches; ability to work with various datatypes including JSON, XML, etc.
  • Familiarity with building data pipelines (e.g. ETL, data preparation, data aggregation and analysis) using tools such as NiFi, Sqoop, and Ab Initio.
  • Practical experience with data lineage processes and management tools, including Avro, Collibra, Denodo, and Trifacta.
  • Basic understanding of Data Science techniques, including: Linear & Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, 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).
  • Experience with model governance processes in a highly regulated industry; financial services preferred.
  • Deliver 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 Cards and Payments, Retail Banking, or Retail Merchant industries preferred.
  • 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.


Leadership Competencies

  • Demonstrates integrity, maturity and a constructive approach to business challenges.
  • Serves as a role model for the organization and implementing core Visa Values.
  • Maintains respect for individuals at all levels in the workplace.
  • Strives for excellence and extraordinary results.
  • Uses sound insights and judgments to make informed decisions in line with business strategy and needs.
  • Able to allocate tasks and resources across multiple lines of business and geographies.
  • Demonstrates ability to influence senior management within and outside Data Science groups.
  • Can successfully persuade/influence internal stakeholders towards building best-in-class solutions.
  • Provides change management leadership.
  • Team oriented, collaborative, diplomatic, and flexible style.
  • Exhibits intellectual curiosity and a desire for continuous learning.
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