Gain uncommon insight into decision-making at the highest levels of business and government, by working directly with expert economists at Matrix Economics on high-profile cases in a variety of industries.

Matrix Economics Careers
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We are committed to creating a vibrant and intellectually exciting office culture with unique opportunities for professionals of all levels.
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Our Analysts gain hands-on experience in coding, data analytics, and project management that enable them to success at top graduate schools. We actively identify and cultivate growth opportunities tailored to individual needs and aspirations.

Matrix Economics


Our Associates learn how to apply their advanced training to solve real-world competition problems in a dynamic, collaborative environment. We help our Associates advance to become active members of the antitrust community.


Matrix Economics offers experienced economists a platform from which to grow. We invest and mentor those who aspire to have leading voices in the antitrust community.




“I like that working at Matrix allows me to apply my statistical toolkit to solve complex real-world economic questions with rigor and creativity. I am constantly learning new things and have improved my communication skills through teamwork.”

– Chongfan, Senior Analyst
Day in the life of—Chongfan


9:10 AM: I board the commuter train and check my work emails on my phone. I start to plan my day to complete the tasks requested by my case manager.

9:45 AM: I arrive at the office and get a cup of green tea and some fresh fruit from the kitchen.


9:50 AM: Using R, I begin to analyze a historical sales dataset from our client. I quickly identify questions related to several data fields. I turn to researching them before continuing with the coding.

11:00 AM: I draft a memo for my case manager that documents my questions, describes the result of my research, and identifies the issues to discuss with him.

11:30 AM: I prepare materials for Matrix’s analyst training program that explains how to perform regressions in R. Meanwhile, my case manager replies to my prior email and asks if we can discuss my memo after lunch. We settle on 1 PM.


12:15 PM: It’s sunny today and my favorite food truck is at Rowes Wharf. I pick up a salad and join my colleagues back in the Shire. We talk about a recently released Marvel movie during the lunch.


1:00 PM: I meet with my case manager to walk him through the questions in my memo. We discuss how to investigate the issues I have identified using other sources of information. We come up with a list of research tasks that I plan to complete over the next two days, one of which is a priority and must be finished today.

2:00 PM: I start working on the prioritized research task. I think about how to present the findings effectively in a chart. My colleagues ask me if I want to join them for a 5 PM yoga class in the gym downstairs. I decline because I want to finish the research task before going home to feed my pet budgies.

4:30 PM: I’m feeling hungry and go to the kitchen for a snack. I struggle to pick between a banana and chocolate chip cookies. After intense deliberation, I choose the cookies.


6:45 PM: I compete the research task and email my case manager the preliminary analysis. I log how I spent my day into our time tracking system, and I leave for home.

8:50 PM: My case manager replies to my email with feedback and questions about the analysis. I answer his questions.


“I love how Matrix has allowed me to work on competition cases in so many different industries. I’ve been able to strengthen my research and data analytics skills and learn from some very experienced mentors.”

– Martin, Senior Analyst
Day in the life of—Martin


9:00 AM: I arrive at the office and check my emails. I start planning my day after grabbing a cup of coffee and a plate of fresh fruit from the kitchen.


9:20 AM: Last night a client sent over a new dataset and requested that we use it to make a table showing their company’s shares. I meet with my case manager to discuss the details of how we should do the calculation.

10:00 AM: I load the dataset into Stata and begin coding the calculation.

11:30 AM: There are some nuances to the analysis that I don’t understand, so I email my case manager my questions and give him an update on how it is going.

11:45 AM: He responds to my questions, and I update my analysis, incorporating his feedback. When I finish, I format the output in Excel to make it presentable.


12:15 PM: It’s time for lunch. It’s a nice day so a few colleagues and I go downstairs. We eat together at tables outside the building.

1:00 PM: I join Ryan and other analysts in a conference room to listen in to a live ABA presentation on the antitrust implications of pharmaceutical rebate walls. After the call, we discuss the questions we had as a group and how the issues relate to some of our casework experience.


2:30 PM: I spend some time putting together a PowerPoint presentation and planning for an evening call we have with the directors of a charity that Matrix has taken on as a pro bono client. Over the past few weeks, I’ve been analyzing their donor database and have a few analyses I’d like to present.

4:00 PM: Hiu Man, Amogha, and I meet to discuss a training session we are putting together on health plan claims data.


5:30 PM: I leave the office and head home on the T.

9:00 PM: Our pro bono client is in a different time zone, so the most convenient time for us to have a videoconference is at night. I join the call from home, present my analysis, and answer their questions. We agree on some research topics I will investigate before our call next month.


“I enjoy my work because the cases we work on are challenging, interesting, and foster curiosity. Matrix is a place where such curiosity is not only welcomed but is also married to precision and intellectual rigor.”

– Amogha, Analyst
Day in the life of—Amogha


9:00 AM: After settling into the office, I stop by my case manager’s desk. He is an Associate I’m working with and briefly discuss the day ahead.

9:30 AM: Our expert requests that we calculate Herfindahl-Hirschman Indices (HHIs) for the markets she has defined in the case. I look into how to operationalize the calculations given the limited sales data on hand.


10:00 AM: Having reviewed the available data, I meet with my case manager to discuss how I plan to code the calculations. We brainstorm potential ways to cross-check the calculations using alternative data.

11:00 AM: I attend a kick-off meeting for a new case. Ryan, who will manage this case, explains the main issues in the litigation, the types of economic analyses we plan to implement, and the case timeline. The case sounds interesting! We allocate initial tasks across the team, which involve researching the industry.


12:00 PM: I head out with colleagues to grab lunch. Our lunchtime conversations are fascinating. Today we are discussing U.S.-Russia relations and the state of the global economy.


1:00 PM: I return to my desk to complete the HHI calculations. I update my case manager, describing the results of my calculations and the data limitations.

2:30 PM: I start on my research task for the new case. I systematically compile targeted information about each competitor in the industry, using each company’s annual reports.

4:30 PM: Our client on the other case just emailed more detailed sales data that will improve the HHI calculations. I review the new data. Thanks to Matrix’s training on best-coding practices, my code requires only minor modifications to accommodate the new data.


5:30 PM: I meet with my case manager to describe the new sales data and present the updated HHIs. We discuss a few follow-on analyses and an expected timeline for completion.

6:00 PM: After the productive meeting, I know exactly what to prioritize when I return to the office tomorrow morning. I head to a nearby T station, to catch the subway home.


“Matrix offers opportunities to solve complex problems while working alongside a diverse team of talented colleagues. I routinely apply my Ph.D. training and have learned essential case management and communication skills. I cannot imagine a better group of people to learn from and work alongside!”

– Joseph, Associate
Day in the life of—Joseph


8:00 AM: After arriving at the office, I check my email and make a to-do list for the day.

8:15 AM: Hiu Man and Amogha stop by my desk to describe a potential new analysis. We brainstorm different approaches and whether a dataset I had previously used could be helpful.

8:45 AM: I start to review the economics literature for another case and concisely summarize the articles I find.


10:00 AM: My teammate and I receive an email from Ryan, who is traveling back to Boston. Ryan lists a series of tasks that will probe the validity of arguments made by an opposing expert at yesterday’s deposition. I meet with my teammate to determine who on the case team is best suited for each task.

11:00 AM: I will work with two analysts—Chongfan and Gina—to address some of the new tasks. Before we meet, I quickly review the opposing expert’s report and think about how best to move forward.

11:30 AM: I explain the big picture of each task to Chongfan and Gina, and we discuss how to structure the work.


12:15 PM: I warm up my lunch and head to the Shire to eat with one of our principals, a fellow associate, and a group of analysts who just returned from the food trucks on the Greenway.


1:00 PM: I work on preparing a new variable to add to the opposing expert’s regression model. At the deposition, the expert asserted that his results are robust to including the variable, and we want to check his assertion.

2:30 PM: Gina asks if we can meet. She has identified a more efficient way to complete her task, and she wants to run it by me. We meet quickly—it’s a great idea that will save several hours of time! I resume my work on the new variable.

5:00 PM: Gina sends me her output, and I review it to ensure the results make sense. I provide feedback on how to improve the formatting and she quickly implements the changes.

5:30 PM: I meet with Chongfan, whose task involves nuanced calculations. I work with her to fully understand the formulas and data.


6:00 PM: My teammate and I meet to discuss the progress on the new tasks.

6:30 PM: I leave work to pick up my dog Bo from daycare and cook dinner before my wife gets home.

8:00 PM: I spend 15 minutes composing an email to Ryan summarizing our progress on the ongoing work. I cc the other case team members to keep them in the loop.


We seek highly-motivated candidates with a passion for solving real-world problems for positions. We place a high value on kindness, effective communication, and a track record of taking the initiative.


We welcome interested undergraduate-level candidates with degrees in economics, statistics, mathematics, or a related subject. We accept applications on a rolling basis. Please see our Analyst job posting.


We welcome interested Ph.D.-level candidates with degrees in economics or related fields. We accept applications on a rolling basis and participate in the American Economic Association’s annual meetings. Associates job posting.

Experienced Professionals

We welcome inquiries from experienced professionals.