Thread by @paulabartabajo_

Do you want to become a freelance data scientist? 😎

Let me share 3 tips in another mega 🧵

#freelancing
#datascience
#machinelearning

The transition from your current 9-to-5 job to remote freelancing is a liberating experience.

The ultimate payoff is immense, including 4 main perks.

Perk #1: higher learning speed, as you are constantly taking in new projects and working with different technologies. This is especially valuable in Data Science and ML, where things are moving very fast.

Perk #2: the opportunity to work with cutting-edge startups, without having to live in a small room in San Francisco.

Perk #3 freedom to organize your days, weeks, and months, plus no one is counting how many vacation days you have taken off this year.

Perk #4 (last but not least) higher hourly rates, which translate into higher paychecks at the end of the month.

The question is, "How can I start working as a freelance data scientist?"

Let me help you with these 3 tips:

Tip #1. Fish in several ponds

There are lots of freelance platforms. I have used 3 of them (Upwork, Toptal, and Braintrust), but feel free to explore others as well.

These platforms can be classified into 2 groups:

- Volume-based platforms, like @Upwork.
There are no entry barriers both for clients and freelancers. Anyone can publish a job, and anyone can register as a freelancer. It is a good place to find small projects, but quite hard to get good clients.

@Upwork • Quality-based platforms, like Toptal or Braintrust.
They have less clients but with higher quality. To see and apply for projects inside these platforms, you need to pass a screening process. It takes around a month to complete, and it is demanding, but the payoff is immense.

@Upwork My recommendation is you create a public profile on Upwork, so clients can contact you from day 0. At the same time, start the application process to make it into a higher-quality platform

Toptal 👉🏽 toptal.com/Bxdpg6/worlds-…
Braintrust 👉🏽 app.usebraintrust.com/r/pau1/

@Upwork Tip #2. Clients look for very specific profiles, for example, someone who knows very well how to either

• analyze a dataset,
• build a dashboard with Tableau,
• build a data pipeline in Google Cloud,
• build a machine learning model,
• scrape a website
• ...

@Upwork It is tempting to try to present yourself as the ultimate freelance data scientist who can do everything, but this is not what the client is looking for.

Data science is a huge market. By narrowing your profile you are still fishing in a pretty large pond. Keep that in mind.

@Upwork Tip #3. 4. Write proposals that solve business problems, not presentation letters

A novice error is to start a proposal like this:

“Dear X. My name is Y, and I am a data scientist with N years of experience in A, B, C, and D. I have a background in E, and … “

@Upwork Sure. Your potential client would love to know about your background. But she is not your mom or dad. He wants to get the problem solved, so go straight to the point. Focus on the problem from the first paragraph. No preambles and presentations that can only make her yawn.

@Upwork My advice is you write proposals like this:

“Hi X! My name is Y. I have built N things recently that are directly related to your problem Z:

• Project 1
• Project 2
• Project 3

I would love to help you with this one. Let’s set a call to get into the specifics. Best, Y.”

@Upwork Freelance remote work as a data scientist is incredibly rewarding, both intellectually and financially. It would give me immense pleasure if any of this advice helped you in your freelance path.

@Upwork If you want to read more about real-world ML and freelancing, follow me on Twitter and subscribe to my newsletter
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