Director Risk Data Science

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

The Director of Risk Data Science is one of the risk roles in the Central Europe, Middle East and Africa (CEMEA) Data Science risk team. We are seeking an innovative and analytical thinker to champion our data-driven strategies within the region. As a Data Science Director, you will participate in building predictive and prescriptive models, and develop context-based prototypes and high-impact storyboards that promote data-driven strategies and solutions for Visa clients. The position will primarily focus on engagements in the area of credit, fraud and operational risks, deep risk analytics, risk scoring as well as forecasting solutions.

Principal Responsibilities

Work entails heavy focus on developing and implementing best-in-class risk analytic solutions, inclusive of scoring and non-scoring models. Create and deliver powerful insights from data through better visualization and storyboarding

Work with a broader team that consists of Business Managers, Consultants and Data Scientists from both Visa and client organisations to strategise, co-create, deploy and reap the benefits of data-driven solutions

Work with regional and global Data Science teams to develop high-quality analytic products and solutions that promote Visas growth in the region

Keep Visa at the forefront of technological advancement in Data Science by introducing cutting-edge tools and techniques for generating business insights

Ability to quickly understand and process alternate / non-conventional data sources / platforms and develop AI based advanced prediction algorithms

Develop next-generation analytic methods where existing tools and techniques are inadequate to address business challenges

Review, direct, guide, and inspire the analytical work of junior members in the team. Manage the India risk DS team who will be reporting directly into

Collaborate with internal Technology partners and Data Engineering function to best leverage Visas internal technology platforms, data, and the broader Visa ecosystem to support our clients technical data needs

Manage workload for self and direct reports, providing prioritization guidance for project flow to improve process efficiency

Develop, share, and build global best practices and knowledge management within the team

Socialize innovative ideas and approaches that are scalable and have market demand

Champion internal requirements around Model Risk Management, Visa Analytics Rules, and Global Privacy standards around client delivery to ensure that Visas highly regarded market standing is maintained

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications

Basic Qualifications

• 10 or more years of work experience with a Bachelor's Degree or at least 8 years of work experience with an Advanced Degree (e.g. Masters / MBA / JD / MD) or at least 3 years of work experience with a PhD

Preferred Qualifications

Technical Expertise

Leadership Competencies

Additional Information

Visa is an EEO 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.

Skills Required

data engineering , Java, Predictive Modeling, Machine Learning, Hadoop, Sas, Postgresql, Scala, Data Mining, Spring Boot, Kafka, Kotlin, Sql, Deep Learning, Risk Management, Elasticsearch, Statistical Modeling, Matlab, Python, Aws, Etl