How can I get an entry-level job as a Data Analyst in NYC, ASAP?

I work in NYC and have been hiring for a fairly quantitative/data-heavy role in finance so I can give you some perspective from the other side. I have been unemployed and hunting for jobs in the past too. Also my wife is a data analyst (and I revamped her resume a ton when she was looking) so hopefully she can chime in. 2) Should I focus mostly on learning SQL and Excel? Yes, become an SQL guru and an Excel wizard. In Excel, at the bare minimum, you should be able to do vlookups and pivot tables in your sleep. Ideally you should be able to code in VBA - actual programming, not just recording macros. Someone who can automate repetitive tasks and make cool spreadsheets with buttons is always in demand. 3) How can I practice each day to build my competency? Maybe come up with your own projects... if you click into my profile I downloaded the Mefi data dump one day, loaded it into SQL server, and did a bunch of statistics for laughs...and I have a job... There's also no shortage of people on Mefi or elsewhere with Excel questions that you could help answer... 6) Most of all, where should I look for these roles? And who should I talk to if I'm serious about getting into data analysis? Personal contacts are huge - contact anyone you know working in these roles - friends, former coworkers or bosses - and ask if they know who's hiring. There's Indeed and LinkedIn obviously but it is just really difficult to get jobs through online postings...which I will talk more about later. Thoughts on the resume: I think your resume is great from a presentation point of view - attractive formatting - but it's not super relevant. Here's what I would change: 1. Put more bullet points on the jobs that you think are most relevant for the job you want; you want to be a data analyst, so talk more about your first 2 jobs. Don't you think it's weird there are 2 bullets each for your music activities and only one bullet for your data analysis job? There should be maybe 3-4 bullets for the first two jobs. Consider removing the two marketing positions at the bottom entirely as they are fairly irrelevant. You don't need to put a bullet for the tutoring job because that is irrelevant to the data analyst job. If you are worried about gaps in your resume (which honestly most people will not even notice) then just list the job title and dates, you don't need to put a description if the job is irrelevant. 2. Remove the activities entirely. You can replace it with one line at the bottom that lists (VERY BRIEFLY) a few of your interests. I don't have interests on mine, but having gone through resumes myself I did feel some kind of affinity with the people who had shared interests. It wouldn't have made me contact someone who was unqualified, but it probably improved my opinion of the "maybes." 3. Remove the scholarship 4. Leave the skills at the bottom, but instead of making a list of 20 things, pick only a few things you are actually good at. Everyone knows "Office suite"... it's taken for granted for anyone born after 1950 or so... but if you're a badass Excel spreadsheet maker and you can code macros and VBA, then highlight that. Likewise, delete "PC & Mac Platforms"...it's a given you can use a computer. "Document design", "Copy editing", and especially "Proofreading" are pretty fluffy and can be removed. On my resume the "skills" section is actual sentences. E.g. "Experienced in doing Blablabla using XYZ programming language." Style choice, I think it reads better. I personally really hate the resumes that have 100 random keywords on them - it's like yeah I know you are trying to get picked up in the HR database or whatever... but in the end a human is reading your resume, and I know that no human could possibly be that skilled in all 100 things. I don't care if you've used it once - I want to know if you're actually any good at it. 5. Remove the music portfolio 6. Remove the sentence under your name...I find "objective statements" or whatever kind of corny... and never understood why those career services people in school claimed they were so important... but they're WRONG! Thoughts on applying for jobs: Only apply to jobs that you are a really good fit for. Indeed and LinkedIn make it WAY too easy for anybody to randomly hit the "apply" button, and most people's lack of effort really shows. I know it's tempting to apply to the "Maybe's" and "What ifs..." but if you're not a good fit for the job, don't bother. Especially if you found it online, then there will be hundreds of other "Maybe" applicants applying that the hiring person has to sort through to find the few good fits. Instead, spend more time on the jobs that you actually have a shot with. If the job description asks for a cover letter, then write one! (I asked for one and maybe 20% of the applicants actually bothered to write one). If the job posting asks you to send your resume to an actual email address, or it's LinkedIn and is posted by an actual person, you've struck gold and should put a lot of effort in - because chances are someone will actually read it! If it's Taleo or one of those generic databases then your resume has a much smaller chance of ever being read by a human, magic keywords or not. Good luck...

You probably need statistics coursework. Maybe this is possible to acquire on your own time from open online classes and texts, but I'm conducting a job search now for similar roles and almost everyone is asking for an undergrad degree in a technical area, or often a graduate degree with evidence of a technical skill set. SQL is only half of the battle; once you're through the ETL process, what are you going to DO with the data? The kinds of tools Ruthless Bunny mentions are nice because they have some of the modeling and data visualization "baked in", but you should really understand some of the stats for yourself. If you can say you know some R, great, because then who cares if Tableau supports exactly the kind of plot you want to make to show your model? You can make it yourself The Data Science specialization on Coursera is nice

So I happen to work in a data analysis position at a nonprofit in NYC. I would recommend that you learn enough SQL to get exactly all the data you want in exactly the right format. Then you can either learn one of SAS/R/Stata, OR you can learn SQL really well, OR you can learn some scripting language like Python.* You should learn basic SQL (because you'll actually need it), and you should learn one of the other to demonstrate that you can "code" to a basic level (this will signal that you will easily be able to pick up whatever language/software your nonprofit decided to use). At a very basic level, you need to convince me that you will not only get the numbers right, but that your data process is clean and well-documented (so that I can QC it). Ideally, it should also be automated so that the requested table/visual/number can be refreshed next week/month/year with minimal effort. Now, since you will be at a disadvantage (non-quantitative background, unemployed), I think you would greatly benefit from writing a blog where you talk about all the cool data scraping you've been doing recently, with insights and accompanying analysis/visualizations. (Really, the folks on the "data teams" are all geeks and will think this is awesome. As long as it's good.) Because you don't have statistics, I think you'd need to be really good on the coding/visualization/data structuring side. Unless the nonprofit is very small, there will be a clear division of labor between grant writers and data folks. For example, most grant writers where I work are your typical English major and don't really "do" numbers or data at all. You might be able to find a niche if you can bridge the two, but it's not exactly standard. * There will be nonprofits that use only Excel, and which have all of their data stored in Excel files on a computer somewhere. These often but not always correspond to those where the "data team" is about 0.6 FTE. You don't want to work there (right now) because you will not be able to acquire the skills that will develop your career. You can work there later on when you have learned what effective data and data management practices look like.

I have had the job you're looking for and was going to answer this question, but all the advice upthread is great. Just go with that and you should be good.

The information on education/skillsets above is fantastic. For specific entry level jobs, I recommend looking into market research. I fell into that out of college with a pretty unrelated degree, and at the job I was able to teach myself all manners of Excel/VBA programming. The pleasure/interest of the work itself will depend heavily on a number of circumstances (work environment, clients, individual projects), and I found that it was easy to go stale if I wasn't actively teaching myself things and working to progress, but it could serve as a really great stepping stone for you. The bigger companies here to look for jobs are Ipsos, Nielsen, Kantar, GfK. There should be a great deal of smaller/boutique companies too, where there may be more room for growth, but you may need to know more going in.

If you do go the market research path, the marketing, and the analysis on your resume will both take you far.