Manager, Data Science
6 months ago
Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.
Job DescriptionConducting transaction data analysis with Hadoop Cloud and big data technologies for internal and external clients and stakeholders, and develop deeper insights into the products using advanced statistical methods.
Creating user-friendly dashboards and presentations.
Building predictive models using advanced machine learning techniques interpret and present modeling and analytical results to non-technical audience.
Executing on the analytic plan with appropriate data mining and analytic techniques.
Performing QA on data and deliverables by analysts and own deliverables.
Ensuring all project documentation is up to date and all projects are reviewed per analytic plan.
Ensuring project delivery within timelines.
Continually look at the environment to challenge our assumptions around new sources of data, potential analytics partners, tools, talent and infrastructure.
Explore leading methodologies and best practices to other teams and importing successful methodologies from other international markets.
This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
QualificationsBachelors degree in Economics, Finance, Computer Science, Statistics, or related quantitative field.
5+ years of experience in performing data exploration and feature engineering and ML models.
Additional InformationVisa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
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