Senior Data Scientist

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 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

Senior Data Scientist

Senior Data Scientist

Overview:

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 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.

Job Title
Senior Data Scientist

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.

Our Team:
Product Data Analytics has pioneered a transaction-based revenue methodology to inform and guide Mastercard’s Strategy, Product Design, and Innovation. We build internal analytics partnerships, strengthening their focus on the health of the business, portfolio and revenue optimization opportunities, initiative tracking, new product development and Go-To Market strategies.

• Are you excited about Data Assets and the value they bring to an organization?
• Are you an evangelist for data driven decision making?
• Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across 6 continents?
• Do you want to be the go-to resource for data science & analytics in the company?

The Role:
• Work closely with global product team to develop an analytic solutions (e.g., dashboards, prototypes), utilizing complex statistical and data science techniques that adhere to best practices and communicate a story on large volumes of data to support data insights across products, markets, and services.
• Drive the evolution of products with an impact focused on data science and engineering.
• Perform data ingestion, aggregation, and processing on high volume and high dimensionality data to drive and enable data unification and produce relevant insights.
• Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations.
• Apply knowledge of metrics, measurements, and benchmarking to complex and demanding solutions.
• Supports junior colleagues by helping with reviewing and debugging their work

All about You
• A superior academic record at a leading university in Computer Science, Data Science, Technology, mathematics, statistics, or equivalent work experience.
• High proficiency in using Python/Spark, Hadoop platforms & tools (Hive, Impala, Airflow), and advanced SQL to build Big Data products & platforms
• Demonstrated success interacting with stakeholders to understand technical needs and ensuring analyses and solutions meet their needs effectively.
• Ability to build a strong narrative on the business value of products and actively participate in sales enablement efforts.
• Able to work in a fast-paced, deadline-driven environment as part of a team and as an individual contributor.
• Ability to easily move between business, analytical, and technical teams, and articulate solution requirements for each group.
• Experience with Enterprise Business Intelligence Platform/Data platform i.e. Tableau, PowerBI, Certification is a plus.
• Knowledge of ML frameworks, libraries, data structures, data modelling, and software architecture is a plus.

Education
• Bachelor’s or Master’s Degree in a Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.S./M.B.A. preferred

Additional Competencies
• Excellent English, quantitative, technical, and communication (oral/written) skills
• Analytical/Problem Solving
• Strong attention to detail and quality
• Creativity/Innovation
• Self-motivated, operates with a sense of urgency
• Project Management/Risk Mitigation
• Able to prioritize and perform multiple tasks simultaneously

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.