All-rounded Data Scientist with 6 years of experience building projects end-to-end and practical knowledge of full-stack web development. Two of my biggest accomplishments are 1) Deploying analytical applications that help investigators much more efficiently catch money-laundering criminals and 2) Creating novel state-of-the-art neural network architecture for makeup detection, recommendation, and virtual try-on
US Census once every year publishes Business Dynamics Statistics (BDS) with 2 year lag. BDS records number of firm births and exits over given year in all sectors and administrative units. The data is published with a 2 year lag, so the most recent data is for year 2021.
I assumed that death rates of firms stays the same as recorded in the birth year of a firm, calculated average lifetime of a firm and probability of surviving after N years and here is what I found:
- Average lifetime for a firm founded in 2016 is 7.6 years
- Average lifetime for a firm founded in 2021 is 6.7 years
- COVID pandemic shortened average lifetime of firm by almost 1 year
- There were 447122 firms founded in 2016;
- There were 478873 firms founded in 2021;
- Only half of them are expected to survive 3 years, only hundred thousand of them will last more than 10 years;
- New York and California are in Top 5 states with lowest average expected firm lifetime - 4.7 and 5.5 years respectively
- South Dakota and Nebraska are the two best states to launch a startup, with average expected firm lifetime of 10.2 and 9.9 years respectively
- If you launch in South Dakota, your start-up will live on average twice longer than if you launched in New York
- The implication of this data is that competition usually outweighs positive network effects when choosing a place to start a business
- Average startups has 49% chance of surviving after 3 years and 20% of surviving after 10 years;
- IT has below average chance of startup surviving after 3 years 45%;
- Arts and entertainment is the most competitive industry with 36% chance of lasting longer than 3 years;
- Utilities is the easiest business to launch with 72% likelihood of become successful, but good luck getting starting capital to launch there;
- Health Care, Agriculture and Finance are good industries to operate at;
- It is a little harder to survive for startups in Transportation and Mining
Check my website for some additional infographics:
I was thinking about the ideas I can work on at free time, and realised they are all not very good, so I decided to work on this project:)
I agree that these listings can be a bit confusing. I set up some simple maths to convert everyones expenditure into revenue per year. So let's say if you put 10$, 2 times a month instead, it would calculate 10$212months = 240$/year, and would sum up over all users that subscribed to the idea.
Since you picked 100$ 12 times per life, I just assumed that you would live around 60 years more (could be optimistic or pessimistic assumption, depending on your age and where you live), which results in 100$*12 times/60 years= $20 per year
It gets even more confusing for ideas that involves monthly subscriptions. Like, let's say I use Netflix once a day, how much am I ready to pay per use? I would put like $15, once a month just to not do mental calculations
Thank you for the feedback! I will have a look into SSR with caching since I am already using Next.js, but I haven't used any SSR functionalities yet. I will add the "cursor:pointers", in general I haven't done much work on design for larger screens yet, just scaled up the mobile version.
At the moment, around half of the content is generated by ChatGPT, and around half by me and my friends. It could be that I am not good at using ChatGPT, but human ideas looked more interesting/fascinating to me
Remote: Yes, but not necessary;
Willing to relocate: Possibly to Toronto, Montreal, New York or Boston
Technologies: Python - PyTorch, Pandas, NumPy, sklearn, PySpark, Prefect, SQLAlchemy, FastAPI; Typescript - Next.js, Redux-toolkit, d3.js;
Resume/CV: https://amethyst-arlene-7.tiiny.site
Email: [email protected]
All-rounded Data Scientist with 6 years of experience building projects end-to-end and practical knowledge of full-stack web development. Two of my biggest accomplishments are 1) Deploying analytical applications that help investigators much more efficiently catch money-laundering criminals and 2) Creating novel state-of-the-art neural network architecture for makeup detection, recommendation, and virtual try-on