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30 year old here. I’m interested in transitioning my career towards programming. Is it worth it to go back to school and get a Master’s in Computer Science (my Bachelor’s is non-STEM)? I know this is a broad question and I’m doing more research into exactly what area of computer science I want to focus on, but I figured I’d ask.
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Feb 2, 2019 06:19
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I have a stem PhD and did a post-doc, for about 6 years of my life my workload was probably about 70% coding (python and ncl) and 30% science and other academic related activities, I also tutor statistics. The biggest project I was working on was using data from 25 global climate models to predict changes, in total about 2000 years of simulation were used. This project was 90% coding and largely data management, looked at multivariable linear regressions but in the end a simple linear regression worked, albeit an enormous amount of data was used. I have been trying to get a data science/data analytics job, anything really and cannot get even a single interview.  In Australia if that matters somehow.
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Feb 2, 2019 06:43
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BattleMoose posted:I have a stem PhD and did a post-doc, for about 6 years of my life my workload was probably about 70% coding (python and ncl) and 30% science and other academic related activities, I also tutor statistics. The biggest project I was working on was using data from 25 global climate models to predict changes, in total about 2000 years of simulation were used. This project was 90% coding and largely data management, looked at multivariable linear regressions but in the end a simple linear regression worked, albeit an enormous amount of data was used. I have an MS in stats (after leaving a PhD program) and it took me a year to find my first job. I did that by going to relevant professional events, like R and python meetups.
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Feb 2, 2019 09:36
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MickeyFinn posted:My lord, The Data Incubator wants me to post a video to YouTube giving them a 1 minute presentation. They also want me to give them the data I scraped. I'm starting to think this might be an actual scam instead of just employment grift.
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Feb 3, 2019 05:53
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I got an email from Dataquest today pushing an interview prep service called Pramp, they pair you with other people who want to practice interviews on the promise that you'll get better job offers. I haven't tried it, and likely won't. The email directs you do a fluff piece by the CEO of Pramp about how to "stand out" in the following way: Refael Zikavashvili posted:Rafi suggests that you send potential employers an email pointing out a challenge that their business is likely facing and how you would solve it. “That will super impress me,” he says. “Somebody who can actually identify problems just based on public information, and more than that will go the extra step and actually suggest a way to solve them? That will blow me away.” The article is, naturally, pushing Dataquest courses so you'll have the skills to waste many hours of your life on a quixotic quest to please someone in the hiring chain of a company who has never heard of you by solving their business problems free of charge. The positional arms race among job seekers is incredible. This reminds me of an interview my brother did with Facebook data science in October 2018. They asked him to come up with an idea for looking for inauthentic accounts. He pitched looking for posts by users in languages other than that spoken in the location the post was made or they usually post in. He added points like checking the currency used by the account and doing a network analysis that checked the poster's friends to see what language they post in. Geohistory for a sudden location change, like on travel. It was a decent on-the-spot pitch. The interviewers said that it was a terrible idea because trolls use VPNs, so location data is useless. Two weeks later this happened: quote:The statement follows a previous announcement from Facebook on Monday, in which the company said it had shuttered 115 accounts — 30 of those being Facebook accounts and 85 being Instagram accounts. It's probably a conspiracy theory to say they stole the idea from him, but given Facebook's lovely history it wouldn't surprise me. It is far more amusing to me that an idea declared stupid in an interview was used literally two weeks later to do the thing it was pitched to do.
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Feb 4, 2019 16:20
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It's so strange, having just read about Data Incubator through this thread one of my physics colleagues mentioned unprompted they were applying for the free fellowship. For what it's worth they did mention that the Data Incubator application homework assignment was significantly harder than the other paid boot-camp programs they'd applied to. Still blown away at the amount of money these boot camps are charging.
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Feb 4, 2019 20:12
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Nocturtle posted:It's so strange, having just read about Data Incubator through this thread one of my physics colleagues mentioned unprompted they were applying for the free fellowship. For what it's worth they did mention that the Data Incubator application homework assignment was significantly harder than the other paid boot-camp programs they'd applied to. Its crazy, right? The business model is pretty simple. They take the recruitment fee from the company that hires you after you complete the camp. That's why they will gladly let people who only need a network go to the camp for free, because they think you'll get a job through whatever network they have. If they are charging you, it is because they don't think they can get the recruitment fee or they are double dipping. Neither is a good sign.
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Feb 4, 2019 21:56
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MickeyFinn posted:That's why they will gladly let people who only need a network go to the camp for free, because they think you'll get a job through whatever network they have. Sounds like a way to get a job. Thousands of hoops to jump and dive through but everything is like that these days.
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Feb 5, 2019 06:48
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MickeyFinn posted:It's probably a conspiracy theory to say they stole the idea from him, but given Facebook's lovely history it wouldn't surprise me. It is far more amusing to me that an idea declared stupid in an interview was used literally two weeks later to do the thing it was pitched to do. Anything is possible. One of the recruiters I work with is involved in a law suit where a company they referred a candidate to brainfucked him and built a product from the interview, apparently. However the example you give is straightforward enough that I find it hard to believe the 100+ data scientists at fb couldn't come up with it on their own.
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Feb 5, 2019 18:40
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As you might expect, I was not accepted to The Data Incubator Fellows program. Was it because my project proposal was a video of Salacious Crumb laughing? Who knows, but there is still hope! Despite me not answering some of the questions either at all or with obvious disdain for the process, I can still pay them:The Data Incubator posted:Dear TDI Applicant, Cattle call round two has begun and it is good to know that my strong data science proposal consisting of this did not go unnoticed. They really pushed the importance of the proposal in their first cattle call: TDI Email #1 posted:By the completion of the challenge we expect: Of course I'm going to apply for the interview. I'm not sure I'll be able to do it, because they likely require me to talk to them at 3 AM my time (I'm in Europe), but if I do make the interview, I've got two questions: (1) What did you think of my proposal? (2) What's up with the 95% of TDI attendees that are not listed on your website? If any of you have any questions I might be able to ask, let me know. If you are earnest I'll ask that question before I likely blow it up. Edit: I have now received my second invitation to the scholar program in 18 hours. Also, they want to assure me that, if I do participate in paying them $17k for a shot at the job market, "only Scholars [and not the tuition-free Fellows] are eligible to interview with non-TDI partners." So, if you're a Fellow they put a hold on your application at a non-TDI partner? MickeyFinn fucked around with this message at 17:58 on Feb 9, 2019 |
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Feb 9, 2019 08:19
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I’m early/mid 30s with a PhD in a STEM-y field and a good job in industry in my field. That said I don’t see a clear path forward for career advancement. The part of my job I enjoy most is writing code (scientific python), but it’s a small part (15% of my time?) and I don’t enjoy the rest. I’ve got a decent offer now, but I am hesitating as it’s below my current salary when I was hoping for a bump. Though I’d rather live in the new city long-term, I have a family and we would be moving away from a big support network. The job itself seems great with room to grow, but the mismatched salary expectations are tempting me to keep looking. Has anyone taken a short-term financial hit to make this transition, and was it worth it? What’s a reasonable starting salary for someone with decent experience but it’s not all relevant? How quickly and how high can someone entering now reasonably expect to rise in the next 5-10 years (maybe the salary range of a senior dev or engineering lead)?
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Feb 10, 2019 16:47
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Sobriquet posted:I’m early/mid 30s with a PhD in a STEM-y field and a good job in industry in my field. That said I don’t see a clear path forward for career advancement. The part of my job I enjoy most is writing code (scientific python), but it’s a small part (15% of my time?) and I don’t enjoy the rest. I did take a big paycut (about 35%, compared to my old engineering salary, to work in an analytics team at a big Tech company). That said, my wife makes as much as me, and so it did not affect our family too much. A year and a half later, I got a 25% pay raise. And a year later, I got an offer from another company with another 20% higher pay on top of that. My old company was willing to counteroffer but I was ready to move on. I'm now a little higher than my old engineering salary, but I think I will have more growth potential. I mostly do Python Pandas and R tidyverse/ggplot/xts time-series stuff. I'd say if you do not enjoy your current job and you think you can do well in analytics, you should go for it. I do not know enough about other people's experience in the industry, but for me, once I owned a lot of the analytics work/projects and can keep the business running with the data insights, you can become valuable quick. The first 25% pay raise I got was the easiest request I ever received (probably because I was underpaid).
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Feb 10, 2019 18:03
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Sobriquet posted:Has anyone taken a short-term financial hit to make this transition, and was it worth it? What’s a reasonable starting salary for someone with decent experience but it’s not all relevant? How quickly and how high can someone entering now reasonably expect to rise in the next 5-10 years (maybe the salary range of a senior dev or engineering lead)? I took a 75% pay cut to move to a job within my field doing machine learning because no one seems to be hiring analysts/ML people without going through a bootcamp first, and they don't seem to take people who aren't already doing the work. So far, it was worth it, while I like the work, everything else sucks as I had to move to Italy to even get the job (my field is DYING) and I'm not a fan, but my old employer was far, far worse and a total dead end. My biggest success in the data science/ML job hunt so far was a rejection email that came the same day I applied. But it seems like you already have an offer, so maybe this response isn't what you are looking for?
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Feb 10, 2019 18:52
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MickeyFinn posted:I took a 75% pay cut to move to a job within my field doing machine learning because no one seems to be hiring analysts/ML people without going through a bootcamp first, and they don't seem to take people who aren't already doing the work. So far, it was worth it, while I like the work, everything else sucks as I had to move to Italy to even get the job (my field is DYING) and I'm not a fan, but my old employer was far, far worse and a total dead end. My biggest success in the data science/ML job hunt so far was a rejection email that came the same day I applied. But it seems like you already have an offer, so maybe this response isn't what you are looking for? The brutes like me that work in implant or etch or IBAD or GCIB or particle therapy or light sources? Meh, it’s a living.
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Feb 10, 2019 23:40
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Tim Thomas posted:High energy accelerator physicists? Absolutely, dead as disco. The vast majority of my work is in industrial, medical and light sources, with a little bit of advanced accelerators. Those are dying pretty badly too. I looked for another job in the field for 3-4 years. The US labs won't touch me because I didn't do a post doc, the US companies won't touch me because I'm not from a lab*, so I had to find a small lab in Europe to try to GTFO. * Seriously, a new "start-up" in radiation therapy went out looking for people to design and build their sources. I didn't even get a call back and 6 months later the company I was working for was building the accelerators because the lab guys they hired don't know how to build poo poo without machinist and technicians with 50-60 years of domain specific knowledge holding their hands.
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Feb 11, 2019 07:40
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I'm doing to double post because I just had The Data Incubator "Scholar" interview. First off, it is a group interview, which was really weird, a whole new meaning to cattle call. But that does mean that I got to see other people present. One was pretty polished and interesting, so cool. The others less so. One was really basic, looking at likes versus location. The quality of the pitches (my own included) was pretty low and since he didn't even mention that my proposal video was of a creature from Star Wars laughing, I'd guess the proposal videos don't really matter at all. The description of the program I got was as follows (I'm going to paraphrase): There are 4 hours of lectures a week and the rest of the time is spent working on projects and doing interviewing/networking. They give you a project every week, tell you a little about it and then leave you to figure it out on your own. The interviewer framed it as a way to build your confidence about learning to tackle problems. He also specifically told me we'd be using Google and reading a lot of documentation. We were strongly encouraged to attend in person because getting help and collaboration is easier in person (note in-person is $17k, remote is $9k). He also said there is a Slack channel for the class in-person and remote alike. This was the answer to my question of what is the most important thing they will teach us. I was expecting "interviewing skills" but I guess a bromide about the value of hard work will do instead. Edit: I forgot to mention the most useful piece of information I got. The use GoToMeeting to do the interview and they won't let you share your desktop, calling it a 'disaster.' I dunno if that is because of technical problems or because of dick pics or what. MickeyFinn fucked around with this message at 13:35 on Feb 13, 2019 |
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Feb 12, 2019 21:15
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MickeyFinn posted:The quality of the pitches (my own included) was pretty low and since he didn't even mention that my proposal video was of a creature from Star Wars laughing, I'd guess the proposal videos don't really matter at all. I'm wondering what other subversive elements can be inserted into this. Consider this a part of figuring it out on your own.
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Feb 12, 2019 23:27
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MickeyFinn posted:There are 4 hours of lectures a week and the rest of the time is spent working on projects and doing interviewing/networking. They give you a project every week, tell you a little about it and then leave you to figure it out on your own. The interviewer framed it as a way to build your confidence about learning to tackle problems. He also specifically told me we'd be using Google and reading a lot of documentation. We were strongly encouraged to attend in person because getting help and collaboration is easier in person (note in-person is $17k, remote is $9k). He also said there is a Slack channel for the class in-person and remote alike. That is such a weird "interview". I just finished Metis, a different bootcamp, in December, and I'm starting a really nice job as a data scientist in two weeks. I also got into the Data Incubator at the paying "Scholar" levels, and I declined because they were a little skittish about the costs and specifics, and I generally got a weird vibe from them. The classroom instruction particularly seems light. At a certain point, the best way to learn data science is to do data science, but Metis had at least two hours of hands-on instruction per day, and frequently more. Metis is also 12 weeks instead of 8, and is comparable in costs. There is an element of selling shovels to the miners about the bootcamps, but Metis was upfront about the costs, and I thought the quality of instruction was on par with, and frequently better than, the traditional schools I attended previously. I'd say my cohort was solid, and they weren't all handpicked geniuses. In my opinion, the most important thing in data science is figuring out how to translate whatever messy human problem you're dealing with into something with labels and features that show some kind of pattern. Once you're at the point where you're running classification algorithms on tidy dataframes, some kind of results are guaranteed. There are always improvements to be made, and that's the difference between craftsmen and people who are hammering away with bits and bobs of code from Stack Overflow, but the first and most important step is framing the problem correctly. I came in with a social sciences PhD, which was really good preparation for figuring out how to ask interesting questions. Metis did not do a great job explaining how to do that in 12 weeks, but on the other hand, it took me five years in a PhD program to figure out research design, so if they were to manage teaching that way of thinking quickly, they'd be downright uncanny.
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Feb 15, 2019 06:12
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Well, I have been accepted as a "Scholar." Their website has a link to an Acceptance Page. The course of googling the projects they give us is scheduled to start on April 1, 2019 (funny day to start...) and I have a week to give them $1000 and a month to give them $16k more. In addition, they don't yet know WHERE I'll be placed and won't know until March 5, about a month before the course starts. It could be Boston, New York, DC or San Francisco. Online is also on option. This is such a mess, you have one month to find short term housing in some of the toughest housing markets in the US. I wonder how many students "prove their dedication to data science" by staying in flop houses for two months? There is a lot of information on the Acceptance Pages, for example, here is the "course list":
There is also a 12-day crash course in python/algorithm/SQL/stats that is a redirect to outside websites. There is a list of their hiring partners which is hundreds long and includes no information on when they placed people, Fellows versus Scholars or how long after completing the program it took to get a job. They do offer a 50% refund "if you remain jobless after 9 months." I don't know if working the counter at McDonald's counts as a job.
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Feb 16, 2019 07:50
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Minor update: I had a round of mock interviews with my bootcamp. This was probably a 2 way street thing, where they vetted our technical interviewing skills but also made sure we weren't going to embarrass the company going out into the wild. The next day I had a phone interview with a medium-sized company, who said they'd pass on a recommendation to the team. I submitted about 10 applications over the past 2 weeks, with that being the only positive response. It would be a back end developer job, but focused on sql, so I should probably bone up on that. Its for sure a mindfuck to actually think about leaving my current field, but it's a 20% bump in pay and sounds like a good place to start.
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Feb 16, 2019 14:34
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Honestly a lot of this sounds really shady. Half the people I know in the field are self taught and have made it largely on their own personal momentum. If you're really apprehensive and think you need a kick start if only for networking, fine, but I don't want people to be discouraged and think they HAVE to do this or else.
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Feb 17, 2019 05:26
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Kim Jong Il posted:Honestly a lot of this sounds really shady. Half the people I know in the field are self taught and have made it largely on their own personal momentum. When did they get started in the field and what were they doing before? What is "personal momentum?" I don't know a single person who works in data science under 40 who wasn't doing data science unofficially (they were doing statistics/data analysis for a company but were not called data scientist or analyst) or didn't go through a boot camp. I'm now also seeing entry level job postings that say work in academia doesn't count toward experience. Having been on the application trail for 2 or so years now, my sense is that the conventional wisdom of (we'll take people with lots of training and little experience) from a few years back is no longer accurate, if it ever was. The positional arms race of job applications suggests that is always true as well and that boot camps are now a necessity. But I welcome you telling me otherwise.
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Feb 17, 2019 08:26
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Anyone looking to break into data science right now should read Data science is different now. It's not a happy read, but it's full of things you need to hear.quote:Since 2012, the data science industry has moved extremely quickly. It’s gone through almost every stage in the Gartner hype cycle. We’ve been through the early adoption phase, the negative press around AI and bias, the second and third rounds of venture capital for companies like Facebook, and are now at the point of high-growth adoption: where banks, healthcare companies, and other Fortune 100 companies that move five years behind the market are also hiring for data science in machine learning.
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Feb 17, 2019 17:20
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While it’s for sure the case that worker supply is closing the gap with employer demand, as somebody who lives in a major tech hub, there are still way more jobs than people to fill them. The other thing to consider is best alternatives. If somebody is hosed working a service industry job, the idea that “well data scientist jobs are slowing down” isn’t that big of a deal. Again, and sure this is only anecdotal, but at this point I know almost a dozen people who went through boot camps who are making 6 figures within 6 months of graduation. Most of those people came from backgrounds in service industry, copy editing, and other non-quant backgrounds. Also all but one of them seem a bit dumb. It’s not guaranteed but a lot of people are economically hosed in their current situation and they need to roll the dice on something to get ahead.
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Feb 20, 2019 00:23
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JIZZ DENOUEMENT posted:as somebody who lives in a major tech hub, there are still way more jobs than people to fill them. Where are these jobs exactly, because they sure as gently caress aren't in Australia.
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Feb 20, 2019 03:10
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I was confused by that Medium post too. Why would you advise people not to apply for open positions? Why would you dismiss master’s degrees in data science when their job placement rates, even for average programs, are super high? There’s a lot of good stuff in there but it’s not particularly good career advice for people looking to get in the field, I feel.
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Feb 20, 2019 03:16
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MickeyFinn posted:I'm now also seeing entry level job postings that say work in academia doesn't count toward experience.  Also, thank you for all the TDI posts you've made in thsi thread. Hilarious and scary at the same time, I was considering them after my PhD but now I'm staying the gently caress away.
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Feb 20, 2019 04:38
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ultrafilter posted:Anyone looking to break into data science right now should read Data science is different now. It's not a happy read, but it's full of things you need to hear. Its weird to read a blog post by someone ridiculing the requirements in job posting who then turns around and lists a bunch of skills they spent 10 years acquiring on the job as basic for entry level now. Fields mature, sure, but I wonder if she realizes she is a part of the problem? I guess she doesn't have a problem because there are 200 applicants for every job opening. The quote from Hinton is taken horribly out of context: Geoff Hinton posted:One big challenge the community faces is that if you want to get a paper published in machine learning now it's got to have a table in it, with all these different data sets across the top, and all these different methods along the side, and your method has to look like the best one. If it doesn’t look like that, it’s hard to get published. I don't think that's encouraging people to think about radically new ideas. The quote is pulled out of context and Hinton's point is literally the opposite of the point she was trying to make. He does his share of whining about the peer reviewers not understanding him, which I totally empathize with, but he goes on to say the juniors will become seniors as the field develops. He is not saying that the field is saturated with juniors. The blog post looks like a poorly sampled attempt at bias reinforcement, rather than saying anything interesting. (Know all the skills on day 1! It is more boring than you think!) BattleMoose posted:Where are these jobs exactly, because they sure as gently caress aren't in Australia. I'm posting during what was supposed to be another interview that I was stood up for, so you're in some kind of company. Whether that company is good, I leave up to you. Suspicious Lump posted:This has to be the weirdest thing I've read. Why would entry level jobs require previous work experience and why would previous work experience not count? Not doubting what you've found, doubting the logic of the company. For obvious reasons I'm back on LinkedIn, so have some more stupid job postings. Here's an entry level position that wants 7+ years experience for a job titled "Data Science Machine Learning Lead." This one is 6-8 years and called "Senior." This one only wants 2+ years with strong knowledge of big data platforms and challenges that come with large scale platforms, I hope your AWS credit is topped up. Leidos only requires 15+ years of experience and a Top Secret clearance. These guys want 4+ years of experience. Doordash wants 2+ years of experience. 6sense (whatever that is) wants 4+ years of experience. I'm just scrolling through a list of "data science" jobs in California on LinkedIn filtered for Entry Level and I haven't skipped one yet, but I did find a job without an experience requirement! You can pay Standford CARE $5900 for a 1 week course of some kind followed by 7 weeks of team work. Holy poo poo, the grift is strong with that one. But with Stanford on your resume, I'd be surprised if it didn't work. Livermore didn't even bother to take experienced out of the title. Another 3+ years experience. Same for Twitter. I guess you could teach data science remotely with only 1 year of experience. Adobe wants 5+ years of experience. UCLA wants someone with a fair number of library-specific knowledge, but at least I didn't literally see x+ years for entry level. Ok, I'm off. If you have less than 3 years of data science experience your options are to teach data science or pay Stanford $6k for a 1 week course. MickeyFinn fucked around with this message at 21:27 on Feb 20, 2019 |
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Feb 20, 2019 20:47
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Suspicious Lump posted:Also, thank you for all the TDI posts you've made in thsi thread. Hilarious and scary at the same time, I was considering them after my PhD but now I'm staying the gently caress away. At this point, no one will find this surprising, but TDI emailed me on Thursday saying TDI Scholars Program - Acceptance Deadline Feb 22 posted:Just a reminder that the deadline to accept your place in our Spring 2019 cohort is TOMORROW - Friday, February 22nd. If you have any final questions please don't hesitate to ask! But I'm not paying $17k to google data science practicalities in *rolls the dice on March 5th* ... Boston and I'm also not going to tell them I'm not going, because I want to see how far this goes. I woke up this morning (Feb 23) to this: Your Data Incubator Admissions Status posted:While we were unable to extend you an offer as a Fellow, we would like to extend you an offer to participate in the next session of The Data Incubator from 2019-04-01 to 2019-05-24 as a Scholar. We only extend this opportunity to a very small group of candidates—though Fellows make up the top 1–2% of our applicants, Scholars comprise the next 2–3%—and you should take pride in the accomplishment! Those dates aren't the next session. They are this session, as in the one I've already missed the Feb 22 deadline for. They've constructed this email to look like they are doing me a favor by letting me carry my Scholar status in to the future, but it looks like they are desperate to fill up the classes. I'm trying to figure out who or what at Cornell has funded TDI as I'm curious what extent they are (or did) fund it and what they think of the description of the course work as "google it yourself." If anyone happens to have an information on it, please let me know! Edit: D'oh, start at wikipedia. MickeyFinn fucked around with this message at 09:05 on Feb 23, 2019 |
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Feb 23, 2019 08:54
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MickeyFinn posted:
If you are in CA, I recommend going to R and possibly other related meetups. I got my first full time job this way fwiw. Also look at angel list job postings - it's easier to get started at a crazy startup.
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Mar 6, 2019 19:50
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Last few weeks of my bootcamp are pretty intense. I’m doing a few phone interviews a week, and finically getting the hang of answering technical questions with confidence but I should probably keep reviewing notes and doing practice problems. We were also slotted into our groups for the final project, which is given as a demo in front of all the tech companies in town. The only two people booted out of the camp for failing the final exam were in my group, so it’s just me and another person, which is probably a good thing. All of this while doing my full time regular job means it’s pretty stressful. It seems the bootcamp waited until the final culling of students to start recommending our names to their network of employers, so thats pretty cool.
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Mar 6, 2019 20:22
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meanolmrcloud posted:Last few weeks of my bootcamp are pretty intense. I’m doing a few phone interviews a week, and finically getting the hang of answering technical questions with confidence but I should probably keep reviewing notes and doing practice problems. We were also slotted into our groups for the final project, which is given as a demo in front of all the tech companies in town. The only two people booted out of the camp for failing the final exam were in my group, so it’s just me and another person, which is probably a good thing. All of this while doing my full time regular job means it’s pretty stressful. Hang in there, buddy. I hope it works out for you. Out of curiosity - did they give you any useful interview prep?
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Mar 6, 2019 21:03
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I am 35 this year! In July of last year I finally got out of a really boring job basically sitting in front of Excel all day (investment banking middle/back-office). I moved into marketing in an smartphone-only retail investment brokerage joint venture. Our new service launches this summer. Without getting too long-winded, it seems I have failed to contribute enough to the "marketing" part of marketing since then. So I have been asked to instead put together some kind of user-focused data strategy, where we try to get actionable insight from what will presumably become a trove of data. Basically, analytics. I have zero background in data science, CS, statistics, or analytics, unless using Google Analytics on a personal blog somehow counts. I've been doing my best to manage expectations, saying that I can only do descriptive analytics for now. If they need diagnostic/predictive than they needed to hire a data scientist, like six months ago. Since this company has made several (IMO) poor decisions--for example putting me in charge of this very thing mere months before launch--my guess is the funding will run dry in 2-3 years when our parents refuse to give us another $50 million when we completely miss our KPIs. I have no plans to go back to my last job, so potentially I will be on the street. That gives me 2-3 years to decide what I want to do with my career. I'm not a trader, salesperson, and apparently not a marketer either (licensed to do all three, but oh well). I noticed that many people in this very thread are have STEM PhDs and still can't get a job. My math ability is "accounting level" at best. On the other hand, I already have a job, and we don't have to deal with any legacy datasets/systems/people. If I can justify it, then it should also be possible to get a budget to hire someone. So I have couple questions: 1) (for the company) If you could start from zero with your analytics framework, what technologies would you/wouldn't you use? Any best practices to follow? For the time being I am starting with the output, so trying to collect KPIs and figuring out what sort of reports and insights management is expecting. I built some sample dashboards in Google Data Portal/Studio but apparently other companies in our group use Tableau for visualization. 2) (for me) Would going further down the data rabbit hole be fruitless for someone with STEM background, or will the (presumably) difficult experience of actually building out the models and framework be significant enough to overcome that? If the latter, while certainly not part of the traditional marketing skillset, I assume learning SQL, Python, and R will help me get more technical? Will 2-3 years be enough time to build those skills? zmcnulty fucked around with this message at 03:20 on Mar 7, 2019 |
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Mar 7, 2019 03:14
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zmcnulty posted:Without getting too long-winded, it seems I have failed to contribute enough to the "marketing" part of marketing since then. So I have been asked to instead put together some kind of user-focused data strategy, where we try to get actionable insight from what will presumably become a trove of data. Basically, analytics. I have zero background in data science, CS, statistics, or analytics, unless using Google Analytics on a personal blog somehow counts. These things may be true, or they may not. Unless there is more than you are telling us, all that we know so far is that a shithole company is telling you that you cannot do these things. Why are you trusting the judgment of some idiots at a company that is clearly showing poor judgment in other areas? I have seen many people told they were "no good" at things like marketing, by people who are loving idiots and themselves had no idea what "good" was for those areas (but of course, as idiots are often arrogant, they usually assumed they knew).
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Mar 7, 2019 17:01
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pokie posted:Hang in there, buddy. I hope it works out for you. Yea, we had a few rounds of mock-formal interviews with some of the directors, who provided jobs and roles at different types of companies to practice aiming for their level of casualness/professionalism. We also had some technical interview prep, where we were given direct feedback and suggestions. Still, I’m very used to soft-science interviews, and it’s stressful to have to recall and nail technical details.
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Mar 7, 2019 17:57
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SlyFrog posted:These things may be true, or they may not. Unless there is more than you are telling us, all that we know so far is that a shithole company is telling you that you cannot do these things. Why are you trusting the judgment of some idiots at a company that is clearly showing poor judgment in other areas? Certainly, they could be wrong in their assessment of my abilities. But that's a discussion for a different thread I. From this thread I was mainly looking for advice should I choose to pivot to a more data-focused path.
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Mar 7, 2019 23:07
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zmcnulty posted:Certainly, they could be wrong in their assessment of my abilities. But that's a discussion for a different thread I. From this thread I was mainly looking for advice should I choose to pivot to a more data-focused path. Okay, gotcha. You just seemed to be writing it as if you believed it, and I wanted to offer an alternative explanation/viewpoint. Carry on. 
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Mar 7, 2019 23:57
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meanolmrcloud posted:Yea, we had a few rounds of mock-formal interviews with some of the directors, who provided jobs and roles at different types of companies to practice aiming for their level of casualness/professionalism. We also had some technical interview prep, where we were given direct feedback and suggestions. Still, I’m very used to soft-science interviews, and it’s stressful to have to recall and nail technical details. Cool. Some of it gets easier - I feel like I have nailed every interview about model creation so far, but a lot of it can be specific little bullshit. It's easy to be anxious about it. I've been at it for 6 years and still get pretty nervous at interviews. Some guy was grilling me on Simpson's paradox today, which is not something I have touched since undergrad.
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Mar 8, 2019 06:22
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zmcnulty posted:So I have couple questions: Unless you're a dumbass, I think most people can learn the statistical techniques used in model building. I would personally focus more on the stats side of things and go easy on the programming aspect, this will come naturally as you learn more and more. Choose one language and just stick with it, don't hop until you feel comfortable in that language. IMO R and python are very close for data science, but R is better at visualisation/data wrangling while python is better at machine learning. You can learn a lot of in 2 years, then hop out and find another job.
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Mar 11, 2019 01:31
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Quick update! My bootcamp ends this week and it looks like our project will be good to go on ‘demo day’. I accepted an offer from one of the bigger companies in the area, pending a background check. It would start at nearly twice my current salary, though I do have to give up a lot of flexibility and work the 9 to 5, whereas now I probably only work about 30 hr per week. I suspect that the bootcamp itself is pretty heavily involved in the process, as the HR manager at the bootcamp has been recommending specific people to specific companies where he thinks they would be a good fit. My interview with them went pretty dang well, and they seemed to know what level of technical questions would be best to still be a challenge, probably because they are fed a lot of bootcamp grads.
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Mar 19, 2019 17:30
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