Lead Data Scientist

**Our Purpose**
- Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential._

**Title and Summary**

Lead Data Scientist

Overview:
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 diverse computing environments, including Linux shell-scripting, Docker, AWS or GCP. DevOps skills is a plus.
- 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 web scraping techniques and/or graphical networks is a plus.

Business Skills:

- 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. Work experience required.

**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.