Data Scientist for Risk and Identity Solutions

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

Are you skilled at turning hard numbers into compelling stories and useful strategic insights? Do you solve complex data challenges with creative flair? Put those skills to work answering strategic questions for one of the world's most respected and innovative payments companies. 

In this role, you will be responsible for a range of duties from basic data analytics, to implementing and delivering advanced machine learning models, visualization solutions and high impact business projects. You will get chance to leverage your business acumen, programming skills, technical knowledge of big data and machine learning techniques. This function is critical in building market-relevant fraud solutions for our clients and intellectual property for Visa. 

The position is based in Atlanta, GA and is a hybrid role. Hybrid employees can alternate between remote and office work. Employees in hybrid roles are expected to work from the office 2-3 days a week (as determined by leadership/site), with a general expectation of being in the office 50% or more of the time, depending on business needs.

Essential Functions

• Validate newly developed risk models, generate performance analysis at the aggregate level, as well as issuer level.  Interpret and present performance results to non-technical audience
• Prepare new model testing packages for production deployment, and support model installations and calibration
• Propel analytic product development via conducting statistical analyses on various data sources, and add values to products by being innovative and applying the analysis
• Find opportunities to create and automate repeatable analyses or build self-service tools for business users
• Support sales and business efforts with sound statistical and financial analysis, execute ad-hoc analyses to meet the fast-changing market demands
• Conduct 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 methods
• Ensure project delivery within timelines and meet critical business needs
• Promote 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

• 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)

Preferred Qualifications

• 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
• A Master’s Degree in a quantitative field, such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering or Bachelor Degree with 2 years’ experience
• Successful internships or 6 month of experience in a predictive modeling function
• 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, 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 multi-tasks in a dynamic environment
• Visa and financial, payment industry knowledge or previous experience with fraud modeling is a plus, but