For several reasons, I mastered out a physics PhD program in the USA, and I am interested in working a data science position. I am wondering what is the best course of action to break into DS.

I have the following related skills:

• Mathematics: Calculus, linear algebra, numerical analysis, differential equations (ODE and partial), and some basic statistics (descriptive statistics, random variables, the normal and binomial distributions, random sampling and sampling distributions, parameter estimation, confidence intervals and significance testing)
• Numerical analysis: I took a numerical analysis class in undergrad and computational physics (Topics: Representation of numbers and errors; methods for the solution of nonlinear equations; numerical integration; interpolation and polynomial approximation; numerical solutions of ordinary differential equations; numerical solutions of systems of equations).
• Prog: Python (scipy, pandas, numpy, astropy, sci-kit learn), R, Julia, C , Mathematica, experience with Unix systems

• Additional experience/Notes:

  • I spent my undergrad years simulating variable stars with a modern 1D stellar evolution code.
  • My graduate work was more in observational astronomy working with FITS files.
  • I also took a "data-enabled physics" course where I gained experience using an MLP Regressor in sci-kit learn to apply regression to exoplanet data.

I am aware there are tons of resources online (currently working through the IBM Professional Data Sciences Certificate) and I would need to build a portfolio, but I do not know where to start, and I am concerned I am at a disadvantage without experience. I am specifically looking for advice as to how to communicate my background/skills gained from my physics education to DS.

Any advice is welcome!