Director, Data Scientist - Cyber Analytics

Job Title: Director, Data Scientist - Cyber Analytics

Overview:

Who is Mastercard?

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.

Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.

The Fraud and Cyber Intelligence team is looking for a Director to lead our team in Toronto, and drive our data science strategy forward by consistently innovating and problem-solving.

Role

The Director of Cyber Analytics will be a key contributor in helping Mastercard develop and deliver actionable insights and products to help issuers, acquirers and merchants reduce fraud. Specifically, the director will:

1. Lead a team focused on data science, AI model development, and integration of disparate fraud and cyber threat related data sources.
2. Develop analytical pipelines to identify merchants and card that may be at risk as early as possible to prevent future fraud.
3. Continue to improve the fraud measurement methodologies and processes to increase accuracy.
4. Actively develop new analytical dashboards to provide fraud information and benchmarks internally and externally.

All About You

We are pursuing a highly motivated individual who has strong customer relationship management and problem solving skills. This individual should be self-driven, have strong achievement orientation, curiosity, and the ability to research, innovate, and lead other data scientists to the newest and most efficient technologies.

Technical Skills

1. Proven experience analyzing large amounts of data to identify trends and gain insights.
2. Experience with statistical analyses tools (e.g., Python, R, SAS).
3. Record of accomplishment in learning and applying new techniques and data analysis languages.
4. Experience with Python and Spark for data manipulation desired.
5. Experience preparing presentations for management/clients that present insights clearly and efficiently.
6. Experience working with big-data database platforms to manipulate and extract information for analysis (e.g., Hadoop, Netezza, Oracle).
7. Experience using Hadoop clusters desired.
8. Comfortable working with multiple languages and operative systems.
9. Familiarity and experience with UNIX highly desired.

Business Skills

1. Strong communication, collaboration, and leadership ability.
2. Subject matter expertise in payments, cards, and/or fraud or proven ability to learn and master new subject matter areas.
3. Creativity, curiosity, and innovation.
4. Ability to think outside the box and constantly strive for more accurate and efficient ways to perform tasks.
5. Experience developing new products/services.
6. Ability to combine knowledge across multiple disciplines to solve problems.
7. Ability to clearly articulate results of analyses, in writing and verbally, and to work effectively with all levels within the organization.
8. Excellent inter-personal skills, able to work with colleagues remotely as well as in-person.

Education

1. Advanced degree in quantitative discipline preferred (e.g., Data Science, Mathematics, Statistics, Computer Science, or Engineering).
2. Strong Interest and course-work (or demonstrated track record) in data analysis, machine learning, and visualization.