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.
The ML Scientist will work with a team to conduct extraordinary research on data analytics and contribute to the long-term research agenda in large-scale data analytics and machine learning, as well as deliver innovative technologies and insights to Visa's strategic products and business. This role represents a phenomenal chance to create key contributions to Visa's strategic vision as a world-leading data-driven company. The successful candidate must have strong academic track record and demonstrate excellent software engineering skills. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.
Our team is focusing on building a new product suite for Visa’s real time payments options! This will have a fraud-management focus and be scaled across many markets at Visa. This suite will also bring ‘real-time fraud monitoring’ into play using the latest in Machine Learning & Deep Learning technologies. We are seeking ML Scientists that come from a wide array of backgrounds with the curiosity about creating something new and exciting for Visa.
Essential Functions
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 two days a week, Tuesdays, and Wednesdays with a general guidepost of being in the office 50% of the time based on business needs.
Basic Qualifications:
Bachelors degree, OR 3+ years of relevant work experiencers degree or 1+ years of relevant work experience and a Bachelors degree
Preferred Qualifications:
• Masters in Computer Science, Operations Research, Statistics, or highly quantitative field with strength in Deep Learning, Machine Learning, Data Analytics, Statistical or other mathematical analysis, OR 2+ years of relevant work experience and a Bachelors degree
• Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks.
• Ability to program in one or more scripting languages such as Perl or Python and one or more programming languages such as Java, C++, or C#.
• Experience with one or more common statistical tools such SAS, R, KNIME, MATLAB.
• recent graduate with a Masters OR 2+ years of work experience with a Bachelor’s Degree in Computer Science, Operations Research, Statistics, or highly quantitative field with strength in Deep Learning, Machine Learning, Data Analytics, Statistical or other mathematical analysis
• Deep learning experience with TensorFlow is a plus.
• Experience with Natural Language Processing is a plus.
• Experience working with large datasets using tools like Hadoop, MapReduce, Pig, or Hive is a plus.
• Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.