Visa's North America Data Science group supports key bank or merchant partners and internal business units by using rich data to build creative solutions that have an immediate impact on the business of highly analytical partners. The group is looking for Data Scientists passionate about using Visa's rich data to tackle meaningful business problems.
Requirements
- Advanced knowledge of databases and engineering concepts with hands on experience with one or more data analytics/programming tools such as Hive/SQL/Spark/Python
- Expertise in the application of predictive modeling and machine learning techniques
- Knowledge of big data engineering stack including Hadoop, Spark, Kafka and other related components
Responsibilities
- Leverage big data and cutting-edge data mining techniques, provide thought leadership in analytic techniques and business applications to unlock the value of Visa’s unique data set
- Lead development of assets supporting scalable analytic approaches capable of being leveraged by data scientists globally.
- Make recommendations and build use cases on new sources of value by addressing the biggest gaps in our data sources in relation to revenue potential.
- Evangelize new analytic approaches for processing big data through internal training, documentation and by leading technical sharing sessions.
- Utilize Hadoop, and related query engines, such as Hive and Impala, to perform advanced data mining.
- Find opportunities to create and automate repeatable analyses or build self-service tools for business users
- Define detailed analytic scope and methodology, and create architecture plans for data assets.
Other
- Lead a team of analysts within Data Science, including project oversight, coaching and professional development
- Ability to inspire highest level of quality/rigor/thought leadership in reports & data analysis
- Guide team in development of actionable solutions and creation of deliverables that effectively communicate the findings and recommendations
- Research industry metrics and business context and bring this context to bear in analyses
- Direct the execution of medium to large analytic projects based on business requirements and desired business outcomes.
- Experience leading teams of 3+ data scientists
- Track record of leading cross-functional efforts including presenting ideas and analysis to various audience levels
