Data Scientist, Advanced Analytics, Ecosystem Risk

**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** Ecosystem Risk Programs** is a Global Risk group that is tasked with the role of upholding the security and integrity of the payment ecosystem through the interdiction of illegal and fraudulent activity. This is achieved through the deployment of risk quality control and/or compliance programs. The programs are deployed through Visa Rules and additional client guidelines and Visa performs quality control leveraging proprietary tools, specialized third party vendors, regional risk teams, and other stakeholders. ERP also works with internal and external stakeholders to further its charter and initiatives.

This position is ideal for an experienced Data Analyst who is passionate about collaborating with business and technology partners in solving challenging illegal and fraudulent activity. You will be a key driver in the effort to define the shared strategic vision for the Ecosystem Risk Programs platform and defining tools and services that safeguard Visa’s payment systems.

Essential Functions
- As a data analyst in ERP team, you will help design, enhance, and build next generation fraud detection and monitoring solutions in an agile development environment
- Develop ongoing Management Information Systems (MIS) that provides oversight in Visa Ecosystem Risk Programs activity, including trends and discovery tool effectiveness
- Translate business problems into technical data problems while ensuring key business drivers are captured in collaboration with product stakeholders
- Independently deliver projects with mínimal supervision, while collaboration with business and technical stakeholders
- Experiment with in-house and third-party data sets to test hypotheses on relevance and value of data to business problems
- Build needed data transformations on structured and unstructured data.
- Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, data mining and statistical techniques.
- Contribute to development of predictive analytics required under the programs
- Able to work on multiple projects and initiatives with different/competing timelines and demands
- Build-out Visa Transaction Laundering Detection models, leveraging AI/ML, that are targeted to the various merchant activities covered under the program

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**:

- 3 years of work experience with a Bachelors Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
- Bachelors or Masters in Computer Science, Operations Research, Statistics, or highly quantitative field (or equivalent experience) with strength in Deep Learning, Machine Learning, Data Mining, Statistical or other mathematical analysis
- Relevant exposure to modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks
- Proficiency in leading-edge areas such as Machine Learning, Deep Learning, Stream Computing and MLOps
- Experience with Python, SQL, PySpark and Hive on data and analytics solutions
- Experience with data visualization and business intelligence tools like Tableau or Power BI
- Excellent analytic and problem-solving capability combined with ambition to solve real-world problems
- Excellent interpersonal, facilitation, and effective communication skills (both written and verbal) and the ability to present complex ideas in a clear, concise way
- Have great work ethics, and be a team player striving to bring the best results as a team
- Ability to work with internal product development and engineering teams to deliver products on schedule and with great quality. Comfortable in a heavily matrixed organization
- Strong analytical and problem-solving abilities, ability to use hard data and metrics to back up assumptions and evaluate outcomes
- Ability to juggle multiple priorities and make things happen in a fast-paced, dynamic environment
- Ability to understand both business and technical concepts

**Preferred Qualifications**: