Company Description|Job Description
Common Purpose, Uncommon Opportunity. Everyone at Visa works with one goal in mind - making sure that Visa is the best way to pay & be paid, for everyone everywhere. This is our global vision & 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 & businesses around the world, enabling them to use digital currency instead of cash & 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 & FIFA World Cup, celebrate teamwork, diversity, & 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 & security of digital currency to people all over the world. Join our team & find out how Visa is everywhere you want to be.
We are seeking an innovative & analytical thinker to work with our Data Science & Consulting teams in the Central Europe, Middle East & Africa (CEMEA) region. The Data Modeler / ETL Developer is expected to deliver prepped & cleansed data from source systems into analytical environments for modeling & development purposes. The role promotes a data-driven solutions approach for Visa's clients (internal & external) by ensuring that consistent sources of certified data are available throughout the organization. Visa's own data assets will be supplemented with client & other third-party sources for ingestion & provisioning as required.
- Serve as an analytics expert in designing, developing & implementing best-in-class data pipelines & ETL methodologies to support business needs.
- Support the internal data community by investigating & mapping available data sources.
- Manage internal catalogue of certified data feeds for use by end data consumers.
- Collaborate with internal & external partners to fully understand business requirements & desired business outcomes.
- Demonstrate execution proficiency in handing multiple medium-to-large analytics projects in a teaming environment that includes the rest of the Data Science & Consulting team.
- Draft detailed scope for assigned projects, addressing suggested methodology, analytics & development plan. Ensure all project documentation is up to date & all projects are reviewed per analytics & development plan.
- Execute on the analytics & development plan with appropriate data mining & analytical techniques.
- Perform quality assurance of data & deliverables for work performed by other Data Scientists & self, including adherence to Visa's Model Risk Management policies.
- Ensure project delivery within timelines & budget requirements.
- Build on team's analytical skills & business knowledge.
- Enhance existing analytics techniques by promoting new methodologies & best practices in the data management field.
- Provide subject matter expertise & quality assurance of complex data-driven analytic projects.
Minimum of 6+ years of data modeling & analysis expertise in developing ETL pipelines (extract, transform, & load) for business outcomes.
Excellent knowledge, experience & understanding of quantitative techniques (modelling, statistics, root-cause analysis, etc.) with a focus on Card & Payments.
Good understanding of the Payments & Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded & merchant portfolios.
Experience working in one or more of the Card & Payments markets around the globe.
Familiarity in working with big data, both structured & 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, & AI-driven tools & technologies.
Experience planning, organizing, & managing multiple large projects with diverse cross-functional teams.
Demonstrated ability to incorporate new techniques to solve business problems.
Demonstrated resource planning & delivery skills.
- Experience in distributed computing environments / big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems & value stores (SQL, Hive, HBase, etc.).
- Ability to write scratch MapReduce jobs & fluency with Spark frameworks.
- Familiarity with both common computing environments (e.g. Linux, Shell Scripting) & commonly-used IDE's (Jupyter Notebooks); proficiency in SAS technologies & techniques.
- Strong programming ability in different programming languages such as Python, R, Scala, Java, Matlab, C++, & SQL.
- Experience in solution architecture frameworks that rely on API's & 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 & analysis) using tools such as NiFi, Sqoop, & Ab Initio.
- Practical experience with data lineage processes & management tools, including Avro, Collibra, Denodo, & 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 & statistical modeling techniques, including Predictive Modeling (e.g., binomial & 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 & budget.
- Very strong people/project management skills & experience.
Ability to travel within CEMEA on short notice.
- Results-oriented with strong problem solving skills & demonstrated intellectual & analytical rigor.
- Good business acumen with a track record in solving business problems through data-driven quantitative methodologies.
- Experience in Cards & Payments, Retail Banking, or Retail Merchant industries preferred.
- Very detailed oriented, is expected to ensure highest level of quality/rigor in reports & data analysis.
- Proven skills in translating analytics output to actionable recommendations & delivery.
- Experience in presenting ideas & analysis to stakeholders whilst tailoring data-driven results to various audience levels.
- Demonstrates integrity, maturity & a constructive approach to business challenges.
- Serves as a role model for the organization & implementing core Visa Values.
- Maintains respect for individuals at all levels in the workplace.
- Strives for excellence & extraordinary results.
- Uses sound insights & judgments to make informed decisions in line with business strategy & needs.
- Able to allocate tasks & resources across multiple lines of business & geographies.
- Demonstrates ability to influence senior management within & outside Data Science groups.
- Can successfully persuade/influence internal stakeholders towards building best-in-class solutions.
- Provides change management leadership.
- Team oriented, collaborative, diplomatic, & flexible style.
- Exhibits intellectual curiosity & a desire for continuous learning.