advice for RA position

[underg2121]

I'm planning on applying for some RA positions at top institutions, and I have some concerns, primarily GPA and grades. (my school is known to be hard with some grade deflation). I was wondering what my chances are for getting into such RA position. And just advice in general will be very helpful :) (which math/econ courses to take, etc, what to do to maximize my chance for top 20's)

 

PROFILE:

Type of Undergrad: Top 20-25 Private Research University

Undergrad GPA: 3.5

GRE: N/A

TOEFL: N/A

 

Math Courses: Calculus I-III (A,A,A), Intro to Proof ©, Intro to Matrix Algebra ©, Advanced Matrix Algebra (A), Discrete Math (B), Differential Equations (A), Algebraic Structures (A), Operations Research (A), Stochastic Methods (A), Linear Algebra (A), Real Analysis I & II (A,A)

Econ Courses: Intermediate Micro, Macro (A, A), Microeconomics I (Grad level; A) Econometrics (B, B), Market Design (B), Econometrics I (Grad level; A)

Letters of Recommendation:

N/A

Research Experience: RA for my macro professor for more than a year, an independent study under him, plan on working with a well-known professor/author for a standard economics textbook

Software Skills: Proficient - STATA, R, SAS, EXCEL, python

Concerns: GPA, grades

Thank you very much.

[underg2121]

b u m p

[underg2121]

also, if anyone has any thought as to whether RA or MA in econ will be better for me, feel free to share your opinion please! :)

[Kaysa]

Can you scrape data using Python?

[startz]

Undergraduates from American universities are far, far more likely to do the RA route rather than an MA.

[underg2121]

Undergraduates from American universities are far, far more likely to do the RA route rather than an MA.

 

Thanks for your input! My concern is, will I have a chance in landing an RA position at a top institution?

[underg2121]

Can you scrape data using Python?

 

Yes, I have experience with that. Is that an important aspect of being a potential RA?

[jjrousseau]

-- deleted my repeat post -- Edited December 26, 2017 by jjrousseau

[jjrousseau]

I'm currently an RA at a top institution and my undergrad GPA was 3.6 at a top 10 liberal arts. Econ major with 5 math classes during UG. I also spent two years at a Fed between UG and the current job, and took one more math class there.

 

While Fed probably makes me a somewhat different applicant than you, it's worth emphasizing that (1) you don't need a perfect GPA to get these positions, and (2) as Kaysa is probably alluding to, these jobs care quite a bit about coding ability and quality.

 

RA's are pretty involved in screening applicants, so I can also say we pass through a decent number of applicants with GPA's around 3.5/3.6 to the second round, which is a coding task. 3.4 or lower is iffy, but that also tends to be because transcripts show weak grades in important courses. Your previous RA work will also help you.

 

So, yes, you can absolutely land an RA job at NBER, SIEPR, etc. You may need a tiny bit of luck to receive the coding task, but if you get it, make sure to give it a right go and really demonstrate your coding and writing ability. For us, at least, that ends up being the dominant signal.

[underg2121]

advice pls :/

[OC7182]

[deleted] Edited December 27, 2017 by OC7182

[underg2121]

I'm currently an RA at a top institution and my undergrad GPA was 3.6 at a top 10 liberal arts. Econ major with 5 math classes during UG. I also spent two years at a Fed between UG and the current job, and took one more math class there.

 

While Fed probably makes me a somewhat different applicant than you, it's worth emphasizing that (1) you don't need a perfect GPA to get these positions, and (2) as Kaysa is probably alluding to, these jobs care quite a bit about coding ability and quality.

 

RA's are pretty involved in screening applicants, so I can also say we pass through a decent number of applicants with GPA's around 3.5/3.6 to the second round, which is a coding task. 3.4 or lower is iffy, but that also tends to be because transcripts show weak grades in important courses. Your previous RA work will also help you.

 

So, yes, you can absolutely land an RA job at NBER, SIEPR, etc. You may need a tiny bit of luck to receive the coding task, but if you get it, make sure to give it a right go and really demonstrate your coding and writing ability. For us, at least, that ends up being the dominant signal.

 

Hi! Thank you so much for your input, really helped a lot :) I had several questions if you didn't mind answering,:

 

1. When during your undergrad did you apply for RA positions? And how many?

 

2. How will B's in econometric courses look? I have A's in advanced math courses and good research experience that involves coding, but got B's in econometrics courses and was wondering how these will hurt me.

 

Thanks so much for your help! :)

[underg2121]

I'm currently an RA at a top institution and my undergrad GPA was 3.6 at a top 10 liberal arts. Econ major with 5 math classes during UG. I also spent two years at a Fed between UG and the current job, and took one more math class there.

 

While Fed probably makes me a somewhat different applicant than you, it's worth emphasizing that (1) you don't need a perfect GPA to get these positions, and (2) as Kaysa is probably alluding to, these jobs care quite a bit about coding ability and quality.

 

RA's are pretty involved in screening applicants, so I can also say we pass through a decent number of applicants with GPA's around 3.5/3.6 to the second round, which is a coding task. 3.4 or lower is iffy, but that also tends to be because transcripts show weak grades in important courses. Your previous RA work will also help you.

 

So, yes, you can absolutely land an RA job at NBER, SIEPR, etc. You may need a tiny bit of luck to receive the coding task, but if you get it, make sure to give it a right go and really demonstrate your coding and writing ability. For us, at least, that ends up being the dominant signal.

 

Thanks for your reply!

[chateauheart]

I'm currently an RA at a top institution and my undergrad GPA was 3.6 at a top 10 liberal arts. Econ major with 5 math classes during UG. I also spent two years at a Fed between UG and the current job, and took one more math class there.

 

While Fed probably makes me a somewhat different applicant than you, it's worth emphasizing that (1) you don't need a perfect GPA to get these positions, and (2) as Kaysa is probably alluding to, these jobs care quite a bit about coding ability and quality.

 

RA's are pretty involved in screening applicants, so I can also say we pass through a decent number of applicants with GPA's around 3.5/3.6 to the second round, which is a coding task. 3.4 or lower is iffy, but that also tends to be because transcripts show weak grades in important courses. Your previous RA work will also help you.

 

So, yes, you can absolutely land an RA job at NBER, SIEPR, etc. You may need a tiny bit of luck to receive the coding task, but if you get it, make sure to give it a right go and really demonstrate your coding and writing ability. For us, at least, that ends up being the dominant signal.

 

underg2121 - the above post is accurate, and probably the best evaluation we can give. You won't benefit from additional opinions from other posters.

[AppliedMicro92]

I fully endorse jjrousseau's advice.

 

As an RA this past year, I've helped my PI review applications for next year's cohort. The vast majority of your duties as an RA will be coding-related, so that's what we focus on when reviewing applicants. Emphasize projects in which you've done a lot of data cleaning, and ask your references to emphasize your coding abilities.

[pulsars]

@appliedmicro92 @jjrousseau Regarding past research experience, does it matter whether the applicant did research in a subfield of economics unrelated to that of the project? For example, the applicant has only RA'd for an IO prof at her school and is doing a thesis on IO, but the project is about health or labor economics and the applicant is seeking more exposure to these applied micro fields. Would that be seen as a positive or a negative?

[jjrousseau]

@appliedmicro92 @jjrousseau Regarding past research experience, does it matter whether the applicant did research in a subfield of economics unrelated to that of the project? For example, the applicant has only RA'd for an IO prof at her school and is doing a thesis on IO, but the project is about health or labor economics and the applicant is seeking more exposure to these applied micro fields. Would that be seen as a positive or a negative?

 

I would say the field of prior research experience matters almost none for RA gigs. For one, few of your competitors are going to have research experience that matches the research in the position you're applying for terribly well, anyway. For another, it's less important that you know specific information coming in, which you can pick up later; it's more important that you're comfortable doing the things RA's do, and that you do it well.

[Kaysa]

Yes, I have experience with that. Is that an important aspect of being a potential RA?

 

Yes, it is the most important aspect other than a positive attitude and good time management skills.

 

Everyone wants to use Python to obtain unique new data sets, so a good background will set you apart.

[kazooie]

Yes, it is the most important aspect other than a positive attitude and good time management skills.

 

Everyone wants to use Python to obtain unique new data sets, so a good background will set you apart.

 

I'm currently an RA at a top institution, and I know several other RAs here as well. While knowing how to use Python and scraping can set you apart, I think that you are overselling its importance. Only two minor things that I have done have involved scraping, and many of my colleagues/fellow RAs have never had to scrape anything.

 

I wanted to add this in case anyone reading this is concerned that them not knowing how to scrape will be disadvantageous: it will not be. I have been helping with the screening process for applicants and not having scraping skills has never been a mark against anyone. That might be a characteristic of the field that the professor for whom I work is in, though (labor).

[Kaysa]

I'm currently an RA at a top institution, and I know several other RAs here as well. While knowing how to use Python and scraping can set you apart, I think that you are overselling its importance. Only two minor things that I have done have involved scraping, and many of my colleagues/fellow RAs have never had to scrape anything.

 

I wanted to add this in case anyone reading this is concerned that them not knowing how to scrape will be disadvantageous: it will not be. I have been helping with the screening process for applicants and not having scraping skills has never been a mark against anyone. That might be a characteristic of the field that the professor for whom I work is in, though (labor).

 

It might not be a mark against, but it sure can be a feather in your cap. Python skills indicate that a candidate has an applied empirical background, a mathematical mindset, and that they can probably solve problems independently. Furthermore, the people that I know that seek out this skill, are the people everyone wants to RA for.

[DisraeliShrugg]

I am clearly late to the party here but thought I can give colour to the above discussion, involving Kaysa and others (Disclaimer: I was an RA at a highly ranked institution, but was never responsible for evaluating applicants.)

 

I think many RA applicants are unaware that RA positions can vary greatly in the way they are managed. Let me give two cases somewhat inspired by reality:

 

1) A junior faculty has obtained access to a "rich" administrative/commercial dataset no one else is using, or has scoped out a way to collect large amounts of data stored on webpages or PDFs. These data have the potential to kickstart a series of papers. With some grant support, the professor hires a RA who will be focused on cleaning, formatting and documenting this dataset.

 

2) A junior faculty has a good pipeline of papers making their way through the review process. The professor needs to revise the papers for submission and hires an RA to speed up the process. The RA's work will involve a mix of augmenting the professor's Stata code and running new analyses suggested by referees (say, run a simulation in MATLAB).

 

The ideal hedge against the uncertainty is to be a CS whiz and have expertise in all the programming languages used in econ - Stata, R, Matlab, Python, ARCGIS, Fortran etc - but this is not realistic for most candidates, even ones at top schools.

 

Now my hunch is that most RA jobs are more like case 1) than case 2). Say you start from scratch. Knowing the above, first you learn Stata, the lingua franca of empirical micro today. Then you invest in languages rising in popularity - Python, GIS, some relational databases. If you still have time, pick up Matlab and R.

 

Most importantly, if you say you know a language you need to show you can use it as part of a research pipeline. This is where cold-calling professors for some data work may land you an opportunity - or take a class with a data analysis project at the end.

 

...with all that said, talking about coding so much is looking at the tree and missing the forest. IMO, the largest constituency RA programs service are top-of-class US Liberal Arts College students who need an intermediary to match them to top PhDs. If you are not in that group, take note of the competition.

[chateauheart]

I am clearly late to the party here but thought I can give colour to the above discussion, involving Kaysa and others (Disclaimer: I was an RA at a highly ranked institution, but was never responsible for evaluating applicants.)

 

I think many RA applicants are unaware that RA positions can vary greatly in the way they are managed. Let me give two cases somewhat inspired by reality:

 

1) A junior faculty has obtained access to a "rich" administrative/commercial dataset no one else is using, or has scoped out a way to collect large amounts of data stored on webpages or PDFs. These data have the potential to kickstart a series of papers. With some grant support, the professor hires a RA who will be focused on cleaning, formatting and documenting this dataset.

 

2) A junior faculty has a good pipeline of papers making their way through the review process. The professor needs to revise the papers for submission and hires an RA to speed up the process. The RA's work will involve a mix of augmenting the professor's Stata code and running new analyses suggested by referees (say, run a simulation in MATLAB).

 

The ideal hedge against the uncertainty is to be a CS whiz and have expertise in all the programming languages used in econ - Stata, R, Matlab, Python, ARCGIS, Fortran etc - but this is not realistic for most candidates, even ones at top schools.

 

Now my hunch is that most RA jobs are more like case 1) than case 2). Say you start from scratch. Knowing the above, first you learn Stata, the lingua franca of empirical micro today. Then you invest in languages rising in popularity - Python, GIS, some relational databases. If you still have time, pick up Matlab and R.

 

Most importantly, if you say you know a language you need to show you can use it as part of a research pipeline. This is where cold-calling professors for some data work may land you an opportunity - or take a class with a data analysis project at the end.

 

...with all that said, talking about coding so much is looking at the tree and missing the forest. IMO, the largest constituency RA programs service are top-of-class US Liberal Arts College students who need an intermediary to match them to top PhDs. If you are not in that group, take note of the competition.

 

That's a very helpful summary and you should stick around to help answer applicant questions related to RA work. Many of the frequent posters here (including me) did not have full-time RA experience before grad school.

[vtuannguyen]

1) A junior faculty has obtained access to a "rich" administrative/commercial dataset no one else is using, or has scoped out a way to collect large amounts of data stored on webpages or PDFs. These data have the potential to kickstart a series of papers. With some grant support, the professor hires a RA who will be focused on cleaning, formatting and documenting this dataset.

 

I am applying to an RA position in top 10 institution. In the second round, they provided me a data set for ticket price from StubHub with a tricky research question. This data set is unconventional, I don't think many people having access to these kinds of data.

[kazooie]

I am clearly late to the party here but thought I can give colour to the above discussion, involving Kaysa and others (Disclaimer: I was an RA at a highly ranked institution, but was never responsible for evaluating applicants.)

 

Great post, DisraeliShrugg! As I mentioned previously in the thread, I am currently an RA at a top institution and have helped with screening applicants. Hopefully my experiences can be useful!

 

I think many RA applicants are unaware that RA positions can vary greatly in the way they are managed. Let me give two cases somewhat inspired by reality:

 

1) A junior faculty has obtained access to a "rich" administrative/commercial dataset no one else is using, or has scoped out a way to collect large amounts of data stored on webpages or PDFs. These data have the potential to kickstart a series of papers. With some grant support, the professor hires a RA who will be focused on cleaning, formatting and documenting this dataset.

 

2) A junior faculty has a good pipeline of papers making their way through the review process. The professor needs to revise the papers for submission and hires an RA to speed up the process. The RA's work will involve a mix of augmenting the professor's Stata code and running new analyses suggested by referees (say, run a simulation in MATLAB).

 

The ideal hedge against the uncertainty is to be a CS whiz and have expertise in all the programming languages used in econ - Stata, R, Matlab, Python, ARCGIS, Fortran etc - but this is not realistic for most candidates, even ones at top schools.

 

I think these two are a fair characterization of what most RA work is (although I would add that you are not limited to a junior faculty being your manager). That said, I'm not so sure that people seeking RA positions should necessarily worry about which one of these two they focus most of their time on. Both options provide enough latitude to distinguish yourself and your work such that you can receive a great letter of recommendation, and learn a lot about the research and publication process. In option 1) there is a surprising amount of independence for how to both assemble the data and create the final sample that you can impress your principle investigator with your ability. Similarly, for option 2) RAs can certainly have an imprint on how to perform suggested analyses by referees.

 

The nightmare scenario that you really want to avoid is a data entry job. To prevent this I think that you should ask the professor if you have been offered the job what they expect you to work on in the first several months of the position, and how they intend for you to do it. A year or two is too long to spend in a position where you have no capacity to impress your professor with your work. Also, ask if the professor has previous RAs with whom you can speak as they might be able to give a good picture of what the work was like.

 

Now my hunch is that most RA jobs are more like case 1) than case 2). Say you start from scratch. Knowing the above, first you learn Stata, the lingua franca of empirical micro today. Then you invest in languages rising in popularity - Python, GIS, some relational databases. If you still have time, pick up Matlab and R.

 

Most importantly, if you say you know a language you need to show you can use it as part of a research pipeline. This is where cold-calling professors for some data work may land you an opportunity - or take a class with a data analysis project at the end.

 

I agree, I think it is unreasonable to expect a candidate to know every useful coding language coming in. When friends ask me where they should start I tell them to master one statistical programming language and develop competency in one object-oriented programming language. For the sort of applied micro research that I do the ideal combination would be STATA and Python, but other fields might have different preferences. You might be surprised, but just knowing two languages well will set you apart.

 

Correctly signaling your knowledge of programming languages is important when it comes to getting your foot in the door. While most RA positions I know of have a programming task intended to test directly your knowledge, that task comes after an initial screening of your resume and cover letter. If you apply to RA positions make sure to provide details on where you learned these language in your cover letter, even if it was just from a course that you took. It is much more credible when an applicant writes "I learned practical programming in Python through a course in numerical applied mathematics, where we implemented several optimization methods including the simplex algorithm and stochastic gradient descent" rather than "I also know how to code in Python".

 

Relatedly, sometimes applicants will write "I am currently learning how to program in Python". This can be much better stated through a short description of how you intend to learn. Say that you are taking a course at your college, or a MOOC, or briefly describe a data set that you want to scrape.

 

...with all that said, talking about coding so much is looking at the tree and missing the forest. IMO, the largest constituency RA programs service are top-of-class US Liberal Arts College students who need an intermediary to match them to top PhDs. If you are not in that group, take note of the competition.

 

Despite my long discussion above of coding, I generally agree. The competition is fierce. Many of the applicants that I reviewed already seemed competitive for top 15 schools. I, however, wouldn't necessarily limit the constituency to just liberal arts college students. The best RA-ships also draw from elite research universities and students who switched to economics later in their undergraduate careers as well.

 

I'm happy to answer any further questions people might have.

[Artemis Yang]

I came from a 40-ish liberal arts college, currently working as an RA at a top 5 institution. My suggestion is to apply as many as you can, as there is so much unexpected randomness in the application process. I applied for about 50 positions last year, got through first round in 13 positions, and received 3 offers (I decided to drop from other applications after I landed on the current one). Previous research experience is not very important. None of the 3 jobs I got matches with my previous research fields in undergrad. Ironically, I didn't even get any response from those few positions that I directly had relevant research experience.

 

Are you also interested in Fed or think tanks? My instinct is that positions at top institutions care more about GPA. Most of the job positions will ask you to do a designed data exercise. Some positions only asked me to show them some codes I wrote for my previous projects. How you perform on the task is probably the most important determinant. Also be sure to express your interests in doing research during the interview.

 

A little more about my current job: I have two supervisors, one is a young assistant professor, one is a senior professor well-known in field. The tasks from the young professor are usually more direct and specific, while the senior professor usually only give general directions and is less concerned with the coding details (there are many other people in the same project btw). The trade-off is obvious: If you work with someone famous, you may not be able to get enough attention from him/her since your professor know so many students who are more talented than you are. If you work with a young faculty member, his/her name will be less noticeable to the admission committee.