Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Essential Functions

Execute model development and performance tracking for risk models, generate performance analysis at the aggregate level, as well as issuer level.  Interpret and present performance results to non technical audience.Compile complex predictive model packages for production deployment, support model installations, and monitor and calibrate production modelsPropel analytic product development via conducting statistical analyses on various data sources, and add values to products by being innovative and applying the analysisFind opportunities to create and automate repeatable analyses or build self service tools for business usersSupport sales and business efforts with sound statistical and financial analysis, execute ad hoc analyses to meet the fast changing market demandsConduct transaction data analyses with Hadoop, Cloud and big data technologies for internal and external product owners, and develop deeper insights into the products using advanced statistical methodsEnsure project delivery within timelines and meet critical business needsPromote big data innovations and analytic education throughout the Visa organization

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.

Qualifications

Basic Qualifications
• 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualifications
• 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
• A Master's Degree in a quantitative field, such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or Engineering
• Preference given to candidates with multiple years working experience in predictive modeling functions
• Candidates with a PhD in a quantitative field, such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering preferred
• Strong background in two or more of the following areas: machine learning, AI algorithms, computations, statistical learning theory, scalable systems (e.g. Spark, Hadoop), large scale data analysis, optimization, functional analysis and deep learning.
• Experience with a range advanced techniques and emerging approaches to big data and data science (Python, Spark, TensorFlow, H2O, Dask, etc),extensive experience with SQL, Hive for extracting and aggregating data
• Good oral and written communication skills and attention to details
• Must be a team player and capable of handling multitasks in a dynamic environment
• Visa and financial, payment industry knowledge or previous experience with fraud modeling is a plus, but not required