datademon

Maybe I haven't looked hard enough: but I still haven't found a service that can reliably do that at the level of detail I need. (Eg. Blacklist all legumes, except for black beans which are whitelisted)

Plus I think that unless the business is focused around these bespoke allergy-friendly recipes, then me blacklisting a large swath of ingredients will lead to me missing out on most of / their best meals.

I would pay a LOT for a meal kit or pre-made meal service that placed allergies/intolerances as its priority.

I suspect the reason this is so difficult is also the reason that I would pay a lot for it: it's a huge pain to come up with many recipes when you're allergic to many things. I'm allergic to almost all legumes. That includes soy, peanuts, lentils, edamame, most beans, peas, licorice, etc. However, I'm not allergic to black beans. This combination of allergies is highly unique: I'm sure there aren't that many people out there who share the exact same allergies. Sure, maybe some people have overlap, but it's likely only a partial overlap.

This means that any meal kit service would either have to 1) Provide bespoke sets of kits for almost every allergy combination possible or 2) Provide a limited number of meal sets that hit the big categories. Option 1 is nigh impossible since that's too many combinations to gain the benefits of economies of scale. Option 2 also sucks because my allergies might get lumped into a broader category and I miss out on ingredients. (Eg. I actually can eat black beans, but since they're legumes, they would likely be banned from a 'no legumes' set of meals)

The closest service I've found is https://paleoonthego.com/collections/aip-bakery

However, I think they fall prey to my option 2's issues. No nightshades??? What the heck? I love tomatoes! Additionally, I haven't even bothered ordering anything from there because the items are so expensive. Just look at some of the prices: $22 for 4 pop tarts! So in fact, not only did they fall prey to option 2's issues, but they also fall prey to option 1's issues! (lack of economies of scale)

I have no idea if this issue is ever solvable in a way that provides a stable business model. Frankly, if normal meal kit services can't make it work, I doubt one that artificially limits its customer base would work either.

Location: Berkeley/San Francisco

Remote: No

Willing to Relocate: To either Seattle/New York/Philadelphia.

Technologies: Python, Jupyter Notebook, WebDev (HTML/JS/PHP), A little bit of AWS

Resume/CV: On request

Email: mpeyton@berkeley.edu

I'm an undergraduate majoring in Data Science at Berkeley. I was previously CS before this major: so I have a solid understanding of software development. I'm looking for a job this summer that could potentially transition into a full time role at the start of 2020. Fall 2019 is my last semester before I graduate. My preferred roles include Data Scientist, Data Engineer, or any sort of Backend/Infrastructure/DevOps role that could take advantage of data.

I did poorly on a math class that was required to declare the major. It's ironic since now that I'm in the data science major, I have to do even more math classes and less programming classes.

I would love to do my own startup. I have a few ideas floating around. But I feel like I lack the discipline to sit down every day and force myself to work on them without external deadlines/pressure.

In terms of jumping into the tech industry: I understand the advice about looking for any job when starting out. It just seems that even a lot of the entry level jobs are very specialized.

As an undergraduate who is about to graduate with a degree in "Data Science" this post encapsulates a lot of my worries as I move into the work world. Should I focus on being a "thinker" a "doer" or a "plumber"? For the first three years I was planning on being a CS major until I was denied from the department: now the data science major is my only hope to graduate. I feel as though my programming skills are solid: but not good enough to be on any sort of fast paced infrastructure/devops team. On the flipside: I feel as though I am so far behind on stats/math knowledge that it's pointless to try and become a data scientist/analyst. I've thought about data engineering (the 'doer') as a happy compromise between the two. However there are barely any intern or entry level data engineering positions that I can find. The ones I do find require knowledge of so many frameworks that I don't know where to start. Additionally, I'm not even sure if data engineering even is a happy compromise, especially after reading the post. Time is ticking, and sooner or later I'm going to have to figure out what route to take, and how I want to specialize. I go to a hyper competitive university in a hyper competitive region of the country and I'm starting to feel like I'm falling behind and getting lost.

If any of you older/more experienced engineers and scientist have advice or wisdom for me, I would very much appreciate it.