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
Manager, Economic Modeling
Overview
The Mastercard Economics Institute (MEI) is an economics lab that drives economic thought leadership in support of Mastercard's efforts to build a more inclusive and sustainable digital economy. The Economics Institute was launched in 2020 to analyze macroeconomic trends through the lens of the consumer to deliver tailored and actionable insights on economic issues for customers, partners and policymakers. The Institute is composed of a team of economists, data scientists and business strategists that utilize & synthesize the anonymized and aggregated data from the Mastercard network together with public data to bring powerful insights to life, in the form of 1:1 presentations, global thought leadership, media participation, and commercial work through our product partners
We are looking for a Causal Inference Economist to join the Economic Modeling team at the Mastercard Economics Institute. The Economic Modeling team is at the forefront of innovations to our Economics products and insights. In this role you will deliver insights using rich datasets, apply and develop econometric and machine learning tools, and work with both internal and external stakeholders at leading companies across different sectors.
Key responsibilities
• Translate broad business questions into well-defined causal effects, identification strategies, and empirical designs
• Develop causal analyses that help clients and internal teams understand the impacts of events, business decisions, market changes, and external shocks
• Lead projects over their full lifecycle – from data ingestion and feature engineering to model validation and communicating the results to key stakeholders
• Guide usage of causal inference tools and of scientific best practices across the team
• Prototype causal inference methods and help turn them into scalable, productized analytics
• Stay current with research methods and experiment with new approaches
About you
• Ph.D. or Master’s in Economics, Econometrics, Marketing, Finance, Public Policy or a closely related quantitative field
• Multiple years of relevant experience in a technically focused environment, although exceptional new PhDs may also be considered
•Proficiency in Python or R, and working knowledge of SQL
• Strong training and experience applying quasi-experimental methods (difference-in-differences, synthetic control, RDD, IV, etc)
• Experience with causal machine-learning methods (double/debiased ML, meta learners, causal forests) and experimentation in a business setting
• Proficient in using AI tools for coding, research, documentation, and rapid prototyping, with appropriate validation and data-governance judgment
• Ability to communicate technical work clearly to non-specialists, in writing and in client presentations
Mastercard is a merit-based, 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. We hire the most qualified candidate for the role. 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.
In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.THIS POSTING IS NOT FOR A CURRENT VACANCY, BUT MASTERCARD IS SEEKING RESUMES TO REVIEW IN THE FUTURE WHEN JOBS BECOME AVAILABLE.
Pay Ranges
Arlington, Virginia: $150,000 - $254,000 USD
Chicago, Illinois: $130,000 - $221,000 USD
Purchase, New York: $150,000 - $254,000 USD