Jobs

Our mission is to eliminate racial disparities in home ownership.
Our company name, Sawa Credit, comes from the phrase "Sawa Sawa" in Swahili, which means "no worries" or "all good."  Black aspiring homeowners should not have to worry more than anyone else when it comes to home loan approval.  Their chances of mortgage approval should be all good, just like anyone else who has shown an ability to successfully manage credit.

To achieve our goal, we are creating an inclusive credit paradigm and provides appropriate leverage to PAPAs (people with Payment Ability Poorly Assessed) in the form of more affordable mortgages.

We are hiring a social science research assistant to help our team review academic literature and real world datasets that are relevant to predicting and influencing consumer financial behavior.

The work will be REMOTE and you will interact with us via telephone and videochat and email. (Of course, we would welcome an in-person visit if you are in the area). You will likely need to frequently avail yourself of your school library and online research resources.  Initially you will be spending a lot of time focused on psychology and economics academic literature, such as writeups of experimental results.

An understanding of statistics and/or data science is preferred because it will enable you to better understand the literature and report on it.

You will work most closely with our marketing and finance teams, both of which are lead by highly experienced professionals.

As you can tell from our mission, we are firm believers in diversity and inclusion. That applies to our team as well!

If you are interested, please send answers to the topics below to This email address is being protected from spambots. You need JavaScript enabled to view it.:
a. your experience with social science research
b. what you (as of now) plan to do after graduation
c. why you chose your major
d. any publications you have authored explaining research results (provide us a link to it or copy of it)
e. any statistics, econometrics, and/or data science experience