Our Purpose

We work 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. We cultivate a culture of inclusion (https://www.mastercard.us/en-us/vision/who-we-are/diversity-inclusion.html) for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.

Title and Summary

Lead Data Scientist

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.

Role

The Lead Data Scientist, Cyber Analytics will be a key contributor in helping Mastercard develop and deliver actionable insights and products to mitigate cyber vulnerabilities across the Mastercard ecosystem. Specifically the incumbent will:

• Develop machine learning models and data pipelines to identify the cyber risk surface for merchants, financial institutions, and relevant third parties.

• Take a leadership role in coordinating across technical and product teams to ensure models are deployed optimally and customer needs are met.

• Communicate insights to both data and non-technical audiences and leverage those insights to innovate data-based solutions to customer problems.

All About You

The Lead Data Scientist, Cyber Analytics will be a key player in helping Mastercard extract value from existing data sources to better detect, understand and prevent cyber vulnerabilities, data breaches, and subsequent fraud.

• You are fundamentally a problem-solver. You like to get into a space and understand the issues. You’re comfortable proposing solutions and working within a cross-functional team to implement that solution. You’re creative, tenacious, and kind.

• You have expertise in data – data manipulation, machine learning, visualizations, pipelines – and are always seeking to learn more. Plus you love sharing that expertise with others, helping the whole team improve.

• You are simultaneously confident and humble, able to work independently but aware that you don’t know everything and comfortable asking for help when it’s needed. You can communicate effectively and persuasively to both technical and non-technical audiences. You advocate for your projects and solutions, but you keep an open mind to alternative proposals.

Technical Skills

• Proven experience analyzing large amounts of data to identify trends and gain insights from it. Familiarity with large-data platforms and languages (e.g., Hadoop, Oracle, Spark)

• Experience with various machine learning techniques and the tools that enable them (e.g., supervised and unsupervised models, reinforcement learning, SQL, Python)

• Knowledge of computing techniques, including SFTP, shell-scripting, UNIX, AWS

• History of creating data stories, leveraging visualizations and/or dashboards to turn data into insights and share those insights with non-technical audiences.

• Knowledge of HTML and web scraping techniques is a plus.

Business Skills

• Subject matter expertise in payments, cyber, and/or fraud or proven ability to learn and master new subject matter areas.

• Creativity and Innovation. Ability to think outside the box and constantly strive for more accurate and efficient ways to perform tasks.

• Strong organizational skills and motivation, with a track record of working independently on expansive goals.

• Strong communication and collaboration. Ability to clearly articulate results of analyses, in writing and verbally, and to work effectively with all levels within the organization.

Education and Work Experience

• Higher-education degree, where you can demonstrate background knowledge of data, coding, and/or cyber (e.g., Mathematics, Statistics, Physics, Engineering, Cybersecurity, Computer Science) or work experience in which you acquired this background knowledge.

• BS , MS PhD. and work experience

• Familiarity with the payments industry and/or cybersecurity, data analysis, and active involvement in that data-to-product development process.

Mastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;

• Ensure the confidentiality and integrity of the information being accessed;

• Report any suspected information security violation or breach, and

• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.