Data Scientist - Senior Consultant Level

Company Description

Visa is a global leader in digital payments, facilitating more than 215 billion payment transactions between consumers, merchants, financial institutions and government entities across over 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.

When you join Visa, you become part of a culture of purpose and belonging – where your growth is our priority, your identity is valued, and your work is meaningful. We believe that economies that include everyone, uplift everyone. Your work will have a direct impact on billions of individuals worldwide – helping unlock financial access to facilitate the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

Payments are an extremely exciting and rapidly developing area with a multitude of new and innovative ideas coming to market. With a high demand for fresh solutions in this field, it promises to be an electrifying sector of innovation. VISA is a formidable leader in the payment industry and is swiftly transitioning into a technology company with significant investments in this area. 

If you aspire to be in the fascinating payment space, learn quickly, and make substantial impacts, Ecosystem & Operation Risk technology, which is part of Visa’s Value-Added Services business unit is the perfect place for you! 

In the Ecosystem & Operation Risk group, the Payment Fraud Disruption team is in charge of building crucial risk and fraud detection and prevention applications and services at Visa. This includes idea generation, architecture, design, development, and testing of products, applications, and services that equip Visa clients with solutions to detect, prevent, and mitigate fraud for Visa and Visa client payment systems. 

This position is ideal for an experienced data scientist who is passionate about collaborating with business and technology partners in resolving challenging fraud prevention problems. You'll play a vital role in the effort to define the shared strategic vision for the Payment Fraud Disruption platform and delineate tools and services that safeguard Visa’s payment systems.

This position is perfect for an experienced data scientist who is enthusiastic about working with business and technology partners in solving complex fraud prevention problems. You'll be an instrumental force in the effort to define the shared strategic vision for the Payment Fraud Disruption platform and outlining tools and services that protect Visa’s payment systems.

The ideal candidate should have a strong background in ML and Data Science, with proven experience in creating, training, implementing, and optimizing advanced AI models for payments, risk or fraud prevention products that added business value and made an impact within the payments or payments risk domain or has experience in building AI/ML solutions for similar industries. 

A successful candidate is a technical leader with the capability to engage in high bandwidth conversations with business and technology partners, think broadly about Visa’s business and drive solutions that will enhance the safety and integrity of Visa’s payment ecosystem. The candidate will contribute to delivering innovative insights to Visa's strategic products and business. This role represents a thrilling opportunity to make significant contributions to Visa's strategic offerings. This candidate should have a strong academic track record and be able to demonstrate excellent software engineering skills. The candidate should be a self-starter comfortable with uncertainty, with exceptional attention to detail, and excellent collaboration skills.

The perfect candidate will bring enthusiasm and passion to use Generative AI to enhance existing fraud detection mechanisms and to create and solve new fraud use cases. This engineer will utilize code generation capabilities like GitHub copilot to increase efficiencies in software development.

Essential Functions

• As a Data Scientist - Senior Consultant, you will help design, enhance, and build the next generation of fraud detection solutions in an agile development environment.

• Formulate business issues as technical data problems while ensuring key business drivers are considered in collaboration with product stakeholders.

• Collaborate with software engineers to ensure the feasibility of solutions. Deliver prototypes and production code based on need.

• Experiment with in-house and third-party datasets to test hypotheses on the relevance and value of data to business problems. 

• Construct necessary data transformations on structured and un-structured data.

• Develop and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as the use of packaged tools based on machine learning, data mining, and statistical techniques. 

• Design and implement methods for adaptive learning with controls on effectiveness, methods for explaining model decisions where necessary, model validation, A/B testing of models. 

• Design and implement methods for efficiently monitoring model effectiveness and performance in production.

• Design and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.

• Contribute to the development and adoption of shared predictive analytics infrastructure.

• Mentor and train other data scientists on the team on key solutions.

• Able to work on multiple projects and initiatives with different/competing timelines and demands. 

• Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate the status, issues, and risks in a precise and timely manner.

• Collaborate across engineering teams and leaders in Ecosystem & Operational Risk, Visa Research, AI Platform, Operations, and Infrastructure (O&I), security and platform teams.

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 three days a week, Tuesdays, Wednesdays, and Thursdays with a general guidepost of being in the office 50% of the time based on business needs.

Qualifications

Basic Qualifications:
8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.
Major in Computer Science, Operations Research, Statistics or a highly quantitative field (or equivalent experience) with an aptitude in Deep Learning, Machine Learning, Data Mining, Statistical or other mathematical analysis.
Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks.
Expert in leading-edge areas like Machine Learning, Deep Learning, Stream Computing and MLOps.
Ability to program in one or more scripting languages such as Perl or Python and programming languages like Java or Scala.
Excellent understanding of algorithms and data structures.
Excellent analytic and problem-solving skill combined with the drive 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 manner.
Great work ethics, being a team player striving to achieve the best results as a team.
High competence in Python, Scala, and Unix/Linux scripts.
Extensive experience with SAS/SQL/Hive for extracting and aggregating data.
Experience working with large datasets using tools like Pig or Hive is desirable.
Experience with Big Data and analytics leveraging technologies like Hadoop, Spark, Scala, and MapReduce.
Deep learning experience working with TensorFlow is necessary.
Experience with Natural Language Processing is necessary.

Preferred Qualifications:
9 or more years of relevant work experience with a Bachelor's Degree or 7 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD.
PhD degree in Computer Science or a related field and 10+ years of Machine Learning System Development Experience after the PhD.
Real-world experience using Hadoop and the related query engines (Hive / Impala).
Experience with one or more common statistical tools such SAS, R, KNIME, Matlab.
Publications or presentations in recognized Machine Learning and Data Mining journals/conferences is a plus.
Experience with data visualization and business intelligence tools like Tableau.
Modeling experience in the card industry or financial service company using for fraud, credit risk, payments is a plus.
Proficiency in designing & solving classification/prediction problems using open-source libraries like Scikit learn.
Experience in developing large-scale, enterprise-class distributed systems of high availability, low latency, & strong data consistency.
Experience developing instrumentation for software components, to help facilitate real-time and remote troubleshooting/performance monitoring.
Experience in architecting solutions with Continuous Integration and Continuous Delivery in mind.
Familiarity with in distributed in-memory computing technologies.

Additional Information

Visa is an Equal Opportunity 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.