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Applying for jobs? Here are crowdsourced tips and advice from our community of 800+ women in econ/policy on writing your best CV for jobs in the space . Long (and very helpful) 
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First the basics - a clean, organised format is key. Limit the usage of unnecessary color, ostentatious fonts etc. It's distracting.
Knowing the ideal length for different types of jobs is important. For some you'd want to submit a one page CV, but for more academic jobs longer CVs are the norm
Customise your CV (not just your cover letter!) based on the job posting (it doesn't have to be hours of work, just moving things around, incorporating skills mentioned in the job description etc)
Quantify and specify your successes! Managed surveys? Write how many. Worked with govt departments? Mention which ones!
Write in reverse chronology with the most recent work/education at the top. Limit the usage of tables. It's a better idea to use bullets as it gives space to speak about specialisations etc.
It is best to drop achievements/experiences that are irrelevant to the job or outdated. Eg.: For an RA job, doesn't require school level achievements. So, it is best to update your CV regularly.
Add links to your website/GitHub/ customised LinkedIn url. Here’s how to get a customised LinkedIn url: https://in.topresume.com/career-advice/customize-linkedin-profile-url
If you haven't written very many research papers, it's still worth adding a Projects section where you can highlight what you have done in your courses (add substantial projects relevant to the job such as blogs, working on a policy brief or a data viz portfolio)
Want to mention Other Interests? Go ahead- it helps to humanise a person in a sea of very similar profiles
On Data work! Add GitHub profile link, and have an application-based repository when you’re on the job market
In your CV- add hyperlinks to your publications, code.
In your CV- add hyperlinks to your publications, code.
Under technical skills: explain what all you have done with the data (sourcing, cleaning, organising, analysing), instead of just writing "analytical work". Elaborate on packages you might have learnt and used. The data you’ve worked on.
Mention what you’re comfortable doing in some programming language. e.g., if you’re good with data cleaning and visualization in R, but are better with web scraping and statistical modeling in Python. Mention that.
Mention if you worked on a team for an internship/RAship, or if you supervised a group of RAs/interns. It gives a good signal especially if you are applying to team-based labs.
RA jobs have a latex-CV. profs/academicians appreciate it if you can work with Latex, and a latex CV is a brilliant way to sort of prove that you can do it. And there’s always Overleaf!
