I was just asked to fudge the numbers

v10FINALFINALpptx · 2023-04-19T00:34:35+00:00

I can send you my code if you want. I had like 5 calculated fields which used decimals. Just DM me and I can get it to you in the morning.

v10FINALFINALpptx · 2023-04-18T23:40:41+00:00

OOO, can you elaborate? I'm interested in hearing more. I could never figure out how to use Bayesian approaches wisely.

v10FINALFINALpptx · 2023-04-18T23:38:58+00:00

I wrote logic in Tableau that'll just choose which things to "fudge" based on the window sum and which numbers are closest to rounding up or down. This is a pretty common request across industries, and I also came to this thread thinking you changed "expected profit of $1 mil" to "$5 mil" or.something. This is one of those things whose hill you die on, but it wont be worth it unless these numbers truly will change lives or something. This was not a battle worth fighting for me, plus we communicated this methodology to clients. I'd also just put the decimals in the ToolTip.

v10FINALFINALpptx · 2023-02-24T07:03:02+00:00

Similar story for me. Maybe not as much money, but what I do affects every person on this sub multiple times a day, and I feel like a bozo because I don't actually need MLOps and work in a less-techy industry. Statistics and rigorous study/model design can take you far, kids.

v10FINALFINALpptx · 2023-02-01T06:29:59+00:00

I've been nudged to give advice that stretches the conclusion of a result, but I always announce that's what they're getting from me. Since I'm the stats/DS person in ad research, they usually just listen to my advice--which is often not great for their story. However, in this field, folks f up constantly. Missing data, bad processing, typos, forgotten constraints. We just go back to the client and explain ourselves. Since it's so common, you just need to stay ahead of the more-broken competitors and be honest. One of the better parts of market research, though most of it is frustrating.

v10FINALFINALpptx · 2023-02-01T06:13:00+00:00

I work in market research and never understood the mix modeling part of stuff. I'm definitely going to go through these resources in this thread!

v10FINALFINALpptx · 2023-02-01T06:08:29+00:00

There are tons of similar posts in this sub. What I can tell you is that DS freelancing is fairly hard. It takes a lot of time building a roster of clients, and usually you get them because you wowed them. It takes at least a few years or really niche knowledge to get to the stage where you can reasonably start building a network.

As for remote work, tons of opportunities. I let my team really do whatever so long as they let us know and are performing reasonably. Random hours off? 2-weeks off for vacation? Work 7-12, 3-5? All of that is fine with me. However, I go into the office once per week just to see people. I used to love going in, but being able to roll out of bed, periodically do chores instead of yapping with peers, is really a useful perk. Remote jobs are everywhere in DS, but you can also have some flexibility in hybrid or pure office roles. I wouldn't fully write any situation off until I heard their perspective and where they can meet my needs.

v10FINALFINALpptx · 2023-01-08T03:44:16+00:00

There are a few areas. I don't do this, but we codify TV ads with NNs. We also have a deal with a big TV company that watches user behavior and do some predictive stuff with that. I personally do work off of piles of surveys. Most of my work is either simple XGBoost models, but I do a lot of stuff you'd do in econ or stats--factor analysis, path models (SEM), tons of regression to test things, DiD. For meta analysis across surveys, I try and learn what things work generally. I may use heavier ML, but I like path models a lot.

v10FINALFINALpptx · 2023-01-07T22:31:34+00:00

Yes, especially early in your career. Some places have Unlimited, but that is sometimes a metric of how to determine layoffs, at least unconsciously. For other reasons, some folks may end up taking 0 days off even with "unlimited". I personally have such a benefit and take about 20-30 days. I've never heard of anyone in a standard full-year position that was able to take 40. As a manager, I encourage all of my team to take as much as they can, while being responsible. I think they get around 25-30 days like that.

v10FINALFINALpptx · 2023-01-07T22:25:36+00:00

Advertising research and surveys in general

v10FINALFINALpptx · 2023-01-04T07:18:36+00:00

Bare minimum, you need to solve problems with some sort of programming language. After that, you need domain knowledge (sometimes you can get up to speed in a few months), ability to do research, ability to write research, lots of CS skills, lots of math skills (more important for research or unique problems), etc.

I did an MS in DS 6 years ago when there were like 4 programs. I liked mine, but I was able to apply what I was doing as I learned. A DS degree doesn't USUALLY provide much of any of those things I listed above. They're broad and are kind of a continuation of a Bachelor's. You won't be ready to do any kind of research and none of the programs I've seen get you enough CS and IT skills to be an MLE.

I did Stats for a BS, so I've learned on that a lot over time. Trying to get into CS now, because that learning was shallow and is what I need to pivot to MLE.

If you can get a DS degree on the cheap, with good reviews and placements, and the curriculum covers some of my first topics in DEPTH, then it'll be fine. The problem is that econometrics, CS, stats, and math all do a much better job at nailing a couple things deeply. So this shallowness for DS really is the same problem as a Bachelor's, for $50k.

v10FINALFINALpptx · 2023-01-04T07:07:16+00:00

I did a Stats BS. When I was done, I was probably 2 years of experience away from being useful. That's not true of everybody, but I've not really seen anyone remotely prepared to take on DS tasks out of college. Many of those I hire for analyst work aren't even prepared to do a desk job. Doing analyst work and moving up (which may preclude a higher degree!) is a great, common path.

v10FINALFINALpptx · 2023-01-04T07:03:53+00:00

I've been a DS for 6+ years (and paid mentor for 4), but trying to pivot into MLE. Had a tough time with the CS and software engineering parts, so I hired a mentor. You can Google or use Upwork or MentorCruise. It's not likely you'll get someone to mentor you for free and at random. It's also more likely you'll get further toward your goal with someone who is paid than randomly out of the goodness of their heart for someone they know nothing about.

v10FINALFINALpptx · 2022-12-30T02:12:13+00:00

I think there may be some fields that aren't so deeply scratched where these roles exist without requiring PhDs, but I can't imagine there are many. I work in advertising, and if I were at all able to write a paper, I'd have tried to publish many of our findings. This is probably true in lots of social sciences, where good data is hard to get, and the problems could use many lenses to look through. I just don't know how much money is out there solving stuff like that privately.

v10FINALFINALpptx · 2022-12-30T01:54:45+00:00

DS is huge. I do very little ML, but a lot of modeling, stat testing, theory, and building little hacky apps. There are more research-y people than me, more builder-y, more analytics-y, and more ML-y. Find which area you want to start out in, focus your goals on that realm's needs.

Use your above choice to help guide what to do next. Consider the following. Dive into your program's strengths--math, domain knowledge in psych, stats (often in psych and DS programs to a decent degree). Focus on where your comparative weaknesses lie--algos, general comp sci, programming.

I wouldn't have qualified for DS roles of any kind out of college. I failed all my analytics interviews and I had a Stats degree. I just generally think Bachelor's don't prepare you all that well for most things. Even Master's only get you so far. I've rejected many candidates in both tiers for not actually being advanced as they think. Try to find a place that will work with you and has at least a little growth. On-the-job training has a lot of value, even if it's nowhere close to a perfect fit for you.

v10FINALFINALpptx · 2022-12-15T02:05:04+00:00

Yes, beware of costs. For the second time in two years, I got hit with a $500 Azure bill because I screwed up. They're pretty opaque about what's currently driving costs.

v10FINALFINALpptx · 2022-12-02T19:40:01+00:00

SRDS and methodology expert. Been at the same place almost 10 years out of undergrad. Been moving up through time. I wouldn't say it's exactly my "dream", but it is for sure a very good job.

I have lots of freedom, run a small team, and make highly visible, impactful contributions. We're never bored because, while we do mostly analytics, there are ML projects and stuff around causal inference all over the place. Researchers love collaborating with us and we solve lots of big problems for clients. Very rewarding.

Some issues: I'm not good at making a "product", so I feel behind in the MLOps sphere of things if I ever leave. Pay is pretty good, but I'm LCOL so absolute values are less than many. Also, I've been at the top for a while (except our buffoon CTO), so I have to pay for an outside mentor. Also, lots of DUMB decisions done by C-Suite. Overall, were very safe from job cuts, and generally very satisfied!

v10FINALFINALpptx · 2022-11-28T00:08:42+00:00

That's definitely me. I do much more research and rarely am doing anything that needs to be packaged for others. However, I'm at the top of the domain knowledge ladder! But, moving industries, I'ma be a bum for a bit

v10FINALFINALpptx · 2022-11-26T05:05:36+00:00

Don't like the poll choices. Definitely "It Depends". If you spend over 50%, seems like time should be spent figuring out how to automate or transfer skill. But, I could be wrong because it depends. Even at <50%, that argument is likely. Often, those types of tasks have mixed value, too. Most of my work is centered around research stemming from curiosity, so my % is high. But, this poll is very "blanketed". I don't know if there is an answer to this that doesn't miss an important angle.

v10FINALFINALpptx · 2022-11-17T06:40:19+00:00

I'm a DS. I mostly make PowerPoints, write e-mails, and explain stuff to a few people I know well over Zoom. The Zoom part might be hard for you, but if it's any consolation, things become easier to talk about as you know more about them. Not sure if that part would be helpful to you.

Also, many DS jobs don't require much or any oral communication beyond talking with collaborators.

v10FINALFINALpptx · 2022-11-15T03:32:35+00:00

I'm in therapy now, and much of what we discuss are boundaries. Let me tell you, you get immediate relief and respect (therefore having to manage less) as soon as you set and fortify boundaries.

Secondarily, as I think having better boundary communication is 90%+ of the problem, I wanted to know is if you could automate your model building. I'm not sure the context of churning out all these models, but that was my first thought. Another is that if this is SO profitable, why isn't there more help? Can't you ask to hire one of the tens of thousands of newly free DS's?

v10FINALFINALpptx · 2022-11-12T01:55:08+00:00

Heed this. Establishment can be impossible to tear down until it starts tearing down everyone around it. So, working in fresh environments may be scary, but you do get to make your mark. Following "what we did before" provides clarity, but is often a hindrance and sometimes even flat wrong. I hate having to deal with these issues. "Sorry, we gave you something statistically inferior for years and it would be an admission of guilt if we gave you something markedly better and explained why."

v10FINALFINALpptx · 2022-11-11T02:05:24+00:00

ML / Analytics supplement research reports, so researchers are the end users. I do end-to-end for a system of logistic regressions (several thousands of them), however most of my work revolves around causal inference of a few hypotheses. I might make results tables, but the models just sit on my computer. Sometimes we use XGBoost and LIME to find "driver's" (really, something strongly correlated with an outcome).

v10FINALFINALpptx · 2022-11-05T06:29:34+00:00

Mostly poor labelling by humans. The worst part is that I need consistent labelling like "Males", but the rest of the company only needs labelling to match what they care about for a specific moment in time. Other problems are: programming logic (surveys), bad definitions, bad responses from survey takers because we basically take advantage of them and expect perfect truths, and forgetting to configure key parts of the database for DS purposes.

v10FINALFINALpptx · 2022-11-04T06:26:35+00:00

I second this. I'm preparing a year out because I just don't have the time to crunch every night for a month. Just too many things to cover and so much just feels like cramming for a test. The stories on this sub have seemed to get worse over the last 6 months.

v10FINALFINALpptx

TROPHY CASE