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I'm looking for some honest feedback on a freelance career plan I've been planning.

My Background:

  • I have a BSc in Math & Physics.
  • I'm about to finish my MSc in Physics (Statistical Physics).
  • My research involved a lot of numerical simulations, so I have substantial project-based experience with Python and C++.
  • The big issue is that I have zero work experience outside of academia (on the other side, I'm a very disciplined and patient self-learner; my degrees required it).

My Goal:

My main goal is to live as a digital nomad for the next 1-2 years, working remotely and part-time (I want the flexibility and freedom to set my own schedule). This is why I'm aiming for freelance projects (on Upwork, Fiverr, etc.) rather than a traditional full-time job.

My 6-8 Month Learning Plan:

I have about 6-8 months of dedicated study time before I plan to start. I've done quite a bit of research and want to focus on skills that leverage my background but are also in high demand.

Here's the "curriculum" I've built for myself, in order of priority:

  1. Python API & Backend: Building a strong foundation with FastAPI, Pydantic, SQL, and Docker.
  2. LLM Application Engineering: I know there might be some hype about it, but I was thinking about learning to build RAG systems, understanding embeddings, vector DBs (like Qdrant), and evaluation/observability.
  3. Applied ML & Analytics: Learning scikit-learn, XGBoost, MLflow, and Statsmodels for common business problems (forecasting, classification, etc.).
  4. Modern Data Tools for Fast ETL: For quick data cleaning and transformation on smaller datasets, working with tools like Polars, DuckDB, and dbt basics.
  5. Scientific Computing & Performance: This directly uses my background. Deepening my knowledge of Numba, CuPy, JAX, and pybind11 to accelerate Python code with C++.

I know that learning the technical stuff is only part of achieving the first projects, so I also plan on investing my time on the following:

  • I'm planning to spend time on building a strong portfolio of 3-4 end-to-end projects with live demos and clean GitHub repos.
  • I'll ensure my LinkedIn profile is client-ready and promotes my technical expertise.
  • I'm fully prepared to start with low wages just to get my foot in the door, and hopefully get good reviews at the beginning.

Based on this long introduction, I would like to ask the following questions:

  1. Are these the right topics? Is this a solid, fundamental stack? Or am I chasing too much "hype" (like LLMs) and setting myself up for risk? Are there "safer" or more fundamental skills I should learn first?
  2. Are these the right roles? I'm aiming for roles like "ML Engineer," "Data Scientist," or "Scientific Software Engineer." Are there other niche roles where my physics/math background provides a better advantage and I'd face less competition for my first gig?
  3. Is this plan realistic?
  • Can I realistically learn this stack to a "hirable" freelance level in 6-8 months?
  • Is it realistic to expect to land any projects with an MSc, a strong portfolio, but zero industry experience (even if I'm bidding low)?

I'd appreciate any feedback, harsh truths, or alternative suggestions. Thanks for reading this long post :)

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Where do you intend on being a nomad? A new graduate with no experience bidding on low cost projects on Fiverr, Upwork, and the like is probably going to be making less than the US minimum wage many months. That might be enough to fund a journey through third-world countries. It probably isn't enough to support yourself if you're planning to travel through Europe. Of course, if you have an alternate source of funds (i.e. parental support) and freelancing just to extend your travel time or to afford "fun stuff", that level of income might be fine. And that's before considering issues with visas and time zones.

How did you come up with the technologies you're going to study? I would suggest that you probably ought to look through the listings on the sites you're targeting and see what people are looking for and what you could realistically bid on. My wager is that you're not going to find a whole lot of data science roles or roles doing scientific computing and a lot more demand for things like building drupal web sites and web scrapers. If your goal is to be competitive for those projects, you'd want to target those technologies rather than things that align with your academic experience. Ideally, you'd find a niche that has regular high-value projects posted and not a lot of competition from other bidders and focus on building your skillset there. But that's pretty optimistic.

Be aware that the most important skills that you'll need to build are not technical. You'll need to be able to sell yourself, estimate project timelines, and manage clients. There are lots of Fiverr & Upwork projects posted by people who are incredibly optimistic (delusional) about how quickly something can be built and lots of bidders that are equally optimistic about how well they understand the requirements and quickly they can build something. Knowing which projects to avoid is probably more important than figuring out which projects you can actually bid on.

You will find yourself at some point in hour 100 of a project you bid at 30 hours because you didn't bake in enough time to deal with some edge cases you didn't know about/ the requirements weren't clear up front/ the client is pushy and is hard to manage. How will you handle that? If you have the ability to work a couple of 60 hour weeks to catch up or you have the ability to manage without income for a month, that's much easier than if you absolutely want to maintain part-time hours.

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