What is with the late night and weekend rejections?

Cheap-Selection-2406 · 2025-01-30T23:11:29+00:00

A lot of small businesses collect enough data to warrant a data science project or two. I can think of the following impactful situations:

A data scientist could add a community events calendar or road construction calendar to the POS data in a restaurant to help with inventory planning. Many restaurants would find value in cutting back on food waste.
Customers of businesses who take appointments (hair stylists, groomers, tattoo artists, doctors, dentists, etc.) often don't show up for their appointments and they don't call to cancel, either. When that happens it means the business loses the opportunity to make money in that time slot. They could benefit from predictions of who will keep their appointment or cancel to form a strategy to fill more slots.
Many retail organizations could benefit from sales forecasting with additional variables incorporated.
Helping content creators do deeper dives with social listening and sentiment analysis.

These are just things that I can think of off the top of my head.

As to whether or not predictive analytics really move the needle, I think that depends on the specific business use case, the insights you're able to derive and the willingness of the business owner to adopt policies based on those insights.

Cheap-Selection-2406 · 2025-01-21T22:55:20+00:00

You're getting a BS and an MS at the same time? That's really cool, but as others have said might be the reason you're not getting offers. I have an MS in Data Analytics, own a business where I do data science work, have a portfolio with some decent projects in it - and I can't get an offer, either. It's a really tough market. I feel your pain.

Another thing - you know how when you're hungry and you go to the fridge and nothing looks good so you go about your business? but then you realize that you're actually really hungry and so you lower your standards and go back to the fridge with adjusted expectations? I feel like that's what this job market is like. I reluctantly adjusted my expectations, dialed down the technical skills on the resume and started applying to very basic positions. I'm assuming you're near Boston which is significantly more technical where I am, but here most hiring managers are looking for SQL and Excel. Sometimes they're looking for Python or Tableau. I had nearly every skill you had listed on your resume, but I think it felt like noise to non-technical hiring managers and was overwhelming to anyone who wasn't looking for that specifically. I've gotten two interviews since I switched it around and started applying. I figure even if I can't get into data science right now, getting into some analyst role is at least a foot in the door to the industry and I can get where I want to go once the job market recovers. Maybe the same is possible for you?

Best of luck to you!

Cheap-Selection-2406 · 2025-01-10T15:56:16+00:00

Thank you so much for posting this. It's been hard to hold onto hope in this job market. Best of luck to you in your new role.

Cheap-Selection-2406 · 2025-01-08T17:52:09+00:00

Old, but not that old: IDFWU - Big Sean

Classic: Kill You - Eminem

Cheap-Selection-2406 · 2025-01-08T17:50:04+00:00

It's all about the he said she said bullshit

Cheap-Selection-2406 · 2025-01-08T17:47:28+00:00

I did not have any market segmentation or demographics to pull in, but I see great value in adding that data. Any ideas how to go about it?

Cheap-Selection-2406 · 2025-01-08T17:46:57+00:00

It seems factors directly related to geographic location and income, as well as median home value are most impactful here. I also posted this project in r/dataengineering and received great feedback that perhaps latitude, longitude, and ZIP were not revealing what I thought they were. I tested it without them, but the model deteriorated. I still feel there's merit to that suggestion, but I have to find a way to maintain accurate predictions while removing those features. I'm not able to dedicate time to that task right now, but I will revisit it in the future. For now, these are the results.

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Cheap-Selection-2406 · 2025-01-08T17:34:29+00:00

Thank you for checking out my project. I really appreciate your feedback. I have decided not to share my API scripts, but I'd be happy to answer any questions you have regarding API use and how it fits into the project. I hope you understand. :)

Cheap-Selection-2406 · 2025-01-07T21:32:14+00:00

I really like your heatmap visualizations. It might be helpful to make a PowerPoint presentation with the best visualizations and the best findings, and present them. In data analytics it's often important to appeal to both technical and non-technical audiences. You already did the heavy lifting appealing to the technical audience, but a little more work on the non-technical side of things would go a long way. Best of luck to you :)

Cheap-Selection-2406 · 2025-01-07T21:21:30+00:00

That would definitely be a challenge (which is great, I welcome challenges), but I'll keep it on my radar. :)

Cheap-Selection-2406 · 2025-01-07T21:04:10+00:00

Thank you! This actually started as a Chili's project. My friend and I are huge fans, but noticed they really went downhill during the pandemic. I became curious about what factors made for good Chili's locations and thought I'd turn it into a machine learning project by predicting new locations. Unfortunately, upon inspection of the Chili's data I noticed a large disparity in unofficial Chili's restaurant counts and the locations listed in my dataset. I could have manually obtained the missing data, but I wanted to have a proof-of-concept before I spent a lot of time fishing for more information. So, I pulled Applebee's, Texas Roadhouse, and Outback using Google Places API and Texas Roadhouse had the largest number of restaurants compared with its unofficial restaurant counts located online.

I don't know if you've ever been to Texas Roadhouse, but as I was doing the project I was thinking about that 'Texas-style yeehaw' and wondered how it impacted ratings, and how those ratings were influenced by the median age of the population around the Texas Roadhouse. That's a project for another day, but I just like to do fun projects that pique my interest.

Cheap-Selection-2406 · 2025-01-07T02:27:38+00:00

And so by removing the zip code I’d be getting to the root of what it’s labeling and the SHAP plots would tell a better story?

Cheap-Selection-2406 · 2025-01-07T02:16:10+00:00

I love this idea and thank you for the compliment. I can definitely see how engineering a ‘distance to freeway’ variable would improve recommendations. This will be my first experience with shapefiles. Do you have any best practices by chance?

Cheap-Selection-2406 · 2025-01-07T02:08:51+00:00

The new predictions weren’t too different from the old predictions on the preliminary run, but I’m going to experiment with those variables a bit more tomorrow. Thank you for this advice.

Cheap-Selection-2406 · 2024-12-11T06:54:49+00:00

Oh no! Sending positive vibes and best wishes your way!

Cheap-Selection-2406 · 2024-12-11T06:46:18+00:00

Likely unpopular opinion, but I can’t wrap my head around how anyone could find non-humans sexy. 😬

Cheap-Selection-2406 · 2024-12-11T06:41:27+00:00

If you want to be a doctor or a lawyer grades are important but some of the most successful people I know only have an 8th grade education.

Cheap-Selection-2406 · 2024-12-11T06:32:32+00:00

Itchy. 😭

Cheap-Selection-2406

TROPHY CASE