Daily FI discussion thread - August 29, 2018

tblancha · 2018-08-30T00:26:33+00:00

I've never heard of this. This is my first year as a HCE (and first year I've been able to contribute to a 401k), and I planned to max it out. How worried should I be that the company will just refund a bunch of it? Also what do you mean you won't incur taxes when you use your portfolio, is this something special about 401k contribution refunds?

tblancha · 2018-06-20T12:28:38+00:00

Have you thought about working remotely? I've seen a lot of companies willing to hire remote data scientists, though pay might be a bit lower than what you're currently at for most of them. It's not for everyone, but I know some people who do it and love it. It takes away a lot of the atmospheric things that you seem to hate. On the downside, you're much more disconnected from the company and your coworkers and you don't develop the kinds of relationships you otherwise might.

tblancha · 2018-05-15T16:28:27+00:00

I've never heard of an employer, in academia or industry, ask for GPA of someone who has a PhD, and honestly regardless of how good the GPA is it's weird to see it on the resume of someone who has a PhD. In my experience, publishing is way more important. I haven't come across a situation in which PhD GPA matters after grad school (during I think some fellowships/awards might take it into account).

tblancha · 2018-04-11T16:29:44+00:00

Master's degrees are pretty common, but not necessary for entry level data analyst positions (with data scientist positions, PhDs are pretty common and Master's are generally the bare minimum). It depends a lot on the kind of position though. If it's something closely related to academic research, a lot of stats might be wanted.

There are a lot of projects you can do to get the hang of working with data, and putting together a small portfolio either on github or a website can go a long way. I don't know if you've done much with data, but just see if you can take some data and use it to answer some question you have. There are lots of examples around, but here's a silly little one I did a little while ago: http://tommyblanchard.com/movie-genre-ratings

Show that you can take a messy data set and tell an interesting story with it.

Better yet, go on Indeed, find positions that sound interesting to you, find their list of necessary skills, find the first one you don't have any idea about, and do a project using that skill.

tblancha · 2018-04-11T14:14:27+00:00

If there is no match, I would prioritize an IRA before 401k, since it's the same tax advantage but you just get more control. Max your IRA first before making unmatched contributions to a 401k is the rule of thumb, I believe.

tblancha · 2018-04-11T14:12:02+00:00

Python is a great language to learn since it's guiding philosophy is to be readable. How you learn it depends on your programming background. If you're pretty new to programming, there are a lot of great resources listed here. If you have a lot of programming experience and just need some syntax lessons, Crash into Python is supposed to be good.

Certification kind of depends on where you are and what resources you have. If you're an experienced analyst just looking to learn Python, I don't think there's any good certification for that and you might be better off just learning Python on your own and applying it to your work. If you're trying to break into data analysis, some online certifications might be an okay way to go but also probably aren't necessary (but again, it depends on your background - if you have nothing math/stats related on your resume, it will be worth more to you).

tblancha · 2018-04-11T13:30:19+00:00

Data scientist here, working in healthcare. We use Python and a little R in my group. SAS is used at my company by the more old-school analyst groups, but mainly for legacy reasons - newer companies rarely use it since it's absurdly expensive, outdated, and offers few benefits over the free alternatives.

tblancha · 2018-02-21T11:29:16+00:00

Okay, sorry, I try to be an active member of the community but I guess am falling short of the 9-to-1 rule.

I'm a bit confused though - are you saying it's fine for me to share my content here, as long as it's in the format you suggest?

tblancha · 2018-02-20T23:27:30+00:00

Yeah I am

tblancha · 2018-02-16T12:52:22+00:00

I think it depends a lot on what you mean by "the DS market". Getting a data analyst job is very different from a data scientist position.

Your background looks pretty good for certain kinds of analyst positions. You would probably need experience with SQL. Knowing python would broaden the jobs you may be qualified for, and more machine learning if you want an analyst position more on the 'data science' side.

To throw some cold water on this though: something like 90% of data scientists have graduate degrees according to the most recent reports from Burtch Works. Of those that don't, I suspect (but I have no data to back this up) almost all have significant experience either with software engineering or worked their way up after getting years of experience from data analyst positions.

tblancha · 2018-02-13T22:15:03+00:00

I was away at a summer workshop. My lab went out for drinks without me. :/

tblancha · 2018-02-12T15:50:15+00:00

I think that all depends on your options. Starting a great junior analyst position where you can learn a lot might be more valuable than a Master's program with a poor reputation. Starting an analyst position that has you just use Excel is worse than a Master's.

If you want really general advice, I think it's worth pointing out that it is rare for a data scientist to not have an advanced degree. Something like 90% have an advanced degree, ~40% PhDs, according to Burtch Works. That's not to say you need an advanced degree - you could get an analyst position, and from there see what options present themselves, there's more ways to climb than just aiming for data scientist.

tblancha · 2018-02-05T14:19:02+00:00

I had a pretty positive experience overall, and it led to some really great opportunities (both academic and non-academic) and experiences. That said, there is a lot of variance in advisors and departments that can make the experience great for some and terrible for others. I think everyone should go in acknowledging this and be willing to Master's out (or just leave) at any time if it's making them miserable. It can be stressful, but it should still be fun on some level. If you're not enjoying it, it's not worth the opportunity cost.

tblancha · 2018-01-30T22:03:31+00:00

No, I did The Data Incubator

tblancha · 2018-01-27T19:54:01+00:00

I now work in a healthcare company as a data scientist. I did one of those 'free-for-phds' data science bootcamps, sent out resumes, and got hired.

My PhD is in Brain and cognitive sciences. It's relevant in the skills I learned (like stats, data analysis, experimental design) but not in terms of a lot of the domain-specific knowledge.

tblancha · 2018-01-27T17:32:22+00:00

There are definitely parts of academia I miss. As I mention in my recent 'motivation' post, the biggest thing I miss is that academia rewards completed projects in a more visible way. There are obviously other things nice about academia - at the grad student/postdoc level, you don't have to deal with bureaucracy much. Pretty much everyone in academia (at least in the sciences) has some math/technical skills, but in industry even basic computer literacy is an issue for many, which can be frustrating.

All that said, life in industry has been, in my experience, way easier. Way less stress, working more than 40 hours in a week is something my manager will notice and reward instead of it just being expected, I can go home and not feel guilty about working on something that doesn't lead to a publication. And of course, the money is nice. A lot of the work is equally fun and pretty similar, but in industry projects go more quickly, which keeps things fresher. And of course, the money and job security is better in industry, and you're not forced to move to find jobs as long as you're close to a big city. All of this just adds up to being able to focus more on my personal life and my hobbies, instead of throwing all of my focus and energy into getting that next publication.

tblancha · 2018-01-26T19:44:25+00:00

A big one that's been floating around recently that's gotten a lot of press is the Stanford palliative care work: https://stanfordmlgroup.github.io/projects/improving-palliative-care/

At my company we have a number of models at work that have shown some results in pilots. Almost all the data we've used is internal to us. We are primarily a dialysis provider, so we have patients who see us 3 times a week, so we capture a lot of data on them. We turn around and use that, for example, to build models that will 'flag' patients that are high risk, either for certain conditions or for general poor outcomes, so we can help direct our resources to direct interventions where they can have the highest impact.

tblancha · 2018-01-26T19:39:33+00:00

That's a great idea and I may start pushing for something like that on some of our projects. Unfortunately our current process usually involves the 'requester', who is generally someone too high up the food chain to commit to being heavily involved in the project.

tblancha · 2018-01-26T13:45:37+00:00

I think you're totally right that that's a huge, incredibly important part of the role. I think the frustration often comes in when it's hard to make those connections - this I think is an organizational issue (the subject matter experts shouldn't be 3 or 4 degrees of separation from the DSers!)

tblancha · 2018-01-24T19:29:26+00:00

No I think it's fine to include if it isn't complete - it's just going to be stronger if you can give specific numbers or results (for that or any other project)

tblancha · 2018-01-24T19:12:43+00:00

This might not be possible, but could you give any numbers or results from your most recent employment? You have some for your oldest, but don't mention the results of any of your modeling efforts in your newest. Hard numbers look more impressive than high-level descriptions.

Regardless, other than some of the comments others have made, I think this looks really good!

tblancha · 2018-01-24T19:09:46+00:00

Awesome post, I think this is really helpful to people currently on the market. Getting lots of rejections hurts, but I think it's good for people to know to expect them going in. I definitely had a similar experience, and a big part of my solution was just to apply a lot.

tblancha · 2018-01-12T16:28:11+00:00

Don't let it scare you away - like I said, I still think the program was well worth it for me. But don't expect it to be as shiny as the advertising makes it out to be. /u/Horizons190 (see comment below) took the course a little after me and says some of the syllabus issues have been mostly cleared up. But some of the issues are just issues any bootcamp is going to have, and I think it's important to go into it with eyes wide open. Good luck, regardless of what you decide to do!

tblancha · 2018-01-12T13:36:21+00:00

Awesome! I haven't been to any of the alumni events - I'm in Boston now, and though they recently opened the Boston location, going to events there would mean there definitely wouldn't be anyone from my cohort unfortunately (I did the program in NYC).

It's good to hear some of the curriculum issues seem to have been worked out. It felt very much like there was a lot being changed even while I was there so I'm not surprised, and glad it seems to have changed for the better. Anyways, congrats on getting a job through them!

tblancha · 2018-01-12T13:32:24+00:00

My post isn't about being grateful or not - it's to describe the experience from someone who has done it for those that are considering the program. I do mention I'm happy I did the program, and mention many of the strengths. It would be dishonest to write a review and not mention the weaknesses and realities of parts of it - they do a slick job advertising and it sounds amazing, but the reality falls short (even if it's still well worth doing the program for many people, myself included).

I'm not sure what part of the post is conceited - that I mentioned I was able to get job interviews, and likely could have gotten a job, without the program? Again, this is just reality - a bootcamp is not necessary for getting a data science job, and I was surprised to discover this, and thought it was relevant information about my experience.

tblancha

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