Remote: Yes

Willing to relocate: No

Technologies: Python, PyTorch, PyData (Pandas, sklearn, etc.), Tensorflow, Docker, GitHub, SQL

Résumé/CV: https://docs.google.com/document/d/1ub1OP5yMZV_UnJUniSSubk5H...

Email: theodorelong98@gmail.com

ML researcher/engineer looking to work on interesting and novel applications of ML. I have previous experience working as a Data Scientist at a NYC hedge fund and am familiar with the full data stack - acquiring, cleaning, analyzing, modeling and putting into production. I've just finished my Masters at the University of Cambridge, focused on ML and computational statistics. During my time there I published a paper: https://openreview.net/forum?id=cFtt9fU7YB6, and worked on a 9 month research project on probabilistic models for Riemannian manifolds for my thesis. I'm a quick learner, but am used to operating in fast-paced, pragmatic environments and getting results. I enjoy working on interesting open-ended problems in pretty much any setting!

Remote: Yes

Willing to relocate: No

Technologies: Python, PyTorch, PyData (Pandas, sklearn, etc.), Tensorflow, Docker, GitHub, SQL

Résumé/CV: https://docs.google.com/document/d/1ub1OP5yMZV_UnJUniSSubk5H...

Email: theodorelong98@gmail.com

ML researcher/engineer looking to work on interesting and novel applications of ML. I have previous experience working as a Data Scientist at a NYC hedge fund and am familiar with the full data stack - acquiring, cleaning, analyzing, modeling and putting into production. I've just finished my Masters at the University of Cambridge, focused on ML and computational statistics. During my time there I published a paper: https://openreview.net/forum?id=cFtt9fU7YB6, and worked on a 9 month research project on probabilistic models for Riemannian manifolds for my thesis. I'm a quick learner, but am used to operating in fast-paced, pragmatic environments and getting results. I enjoy working on interesting open-ended problems in pretty much any setting!

Remote: Yes

Willing to relocate: No

Technologies: Python, PyTorch, PyData (Pandas, sklearn, etc.), Tensorflow, Docker, GitHub, SQL

Résumé/CV: https://docs.google.com/document/d/1ub1OP5yMZV_UnJUniSSubk5H...

Email: theodorelong98@gmail.com

ML researcher/engineer looking to work on interesting and novel applications of ML. I have previous experience working as a Data Scientist at a NYC hedge fund and am familiar with the full data stack - acquiring, cleaning, analyzing, modeling and putting into production. I've just finished my Masters at the University of Cambridge, focused on ML and computational statistics. During my time there I published a paper: https://openreview.net/forum?id=cFtt9fU7YB6, and worked on a 9 month research project on probabilistic models for Riemannian manifolds for my thesis. I'm a quick learner, but am used to operating in fast-paced, pragmatic environments and getting results. I enjoy working on interesting open-ended problems in pretty much any setting!

Remote: Yes

Willing to relocate: No

Technologies: Python, PyTorch, PyData (Pandas, sklearn, etc.), Tensorflow, Docker, GitHub, SQL

Résumé/CV: https://docs.google.com/document/d/1ub1OP5yMZV_UnJUniSSubk5H...

Email: theodorelong98@gmail.com

ML researcher/engineer looking to work on interesting and novel applications of ML. I have previous experience working as a Data Scientist at a NYC hedge fund and am familiar with the full data stack - acquiring, cleaning, analyzing, modeling and putting into production. I've just finished my Masters at the University of Cambridge, focused on ML and computational statistics. During my time there I published a paper: https://openreview.net/forum?id=cFtt9fU7YB6, and worked on a 9 month research project on probabilistic models for Riemannian manifolds for my thesis. I'm a quick learner, but am used to operating in fast-paced, pragmatic environments and getting results. I enjoy working on interesting open-ended problems in pretty much any setting!

  Location: New York
  Remote: Yes
  Willing to relocate: No
  Technologies: Python, PyTorch, PyData (Pandas, sklearn, etc.), Tensorflow, Docker, GitHub, SQL
  Résumé/CV: https://docs.google.com/document/d/1ub1OP5yMZV_UnJUniSSubk5HRWvkBdyPdPEGvHaZmEQ/edit?usp=sharing
  Email: theodorelong98@gmail.com

https://www.juliahomotopycontinuation.org/

I haven’t been able to find much discussion about the specific trade offs in both, and how they compte from a practical perspective.

Hi, I'm Theo. I'm currently finishing up my Master's in CS at the University of Cambridge, with a focus on geometrically-inspired approaches to ML.I'm looking for ML Engineer/Data Scientist jobs in NYC (where I lived and worked prior to my degree), but am open to remote jobs in the US generally (and am a US citizen so no visa requirements). Open to almost any industry, my number one criteria is working on interesting analytical and engineering problems! My previous experience was as a data scientist at a hedge fund, working on leveraging alternative data to analyze private investment opportunities. I'm comfortable getting my hands dirty with messy datasets, building my own ETL pipelines, and working on challenging, ill-defined analytical problems that require creative solutions. Technology-wise I'm best in python, including the usual DS stack (pandas/sklearn etc.), and am experienced with DL libraries (mainly PyTorch, some JAX/TF), and probabilistic programming/bayesian statistics libraries (PyMC3, BoTorch).

Hi, I'm Theo. I'm currently finishing up my Master's in CS at the University of Cambridge, with a focus on geometrically-inspired approaches to ML.I'm looking for ML Engineer/Dat Scientist jobs in NYC (where I lived and worked prior to my degree), but am open to remote jobs in the US generally (and am a US citizen so no visa requirements). Open to almost any industry, my number one criteria is working on interesting analytical and engineering problems! My previous experience was as a data scientist at a hedge fund, working on leveraging alternative data to analyze private investment opportunities. I'm comfortable getting my hands dirty with messy datasets, building my own ETL pipelines, and working on challenging, ill-defined analytical problems that require creative solutions. Technology-wise I'm best in python, including the usual DS stack (pandas/sklearn etc.), and am experienced with DL libraries (mainly PyTorch, some JAX/TF), and probabilistic programming/bayesian statistics libraries (PyMC3, BoTorch).

Hi, I'm Theo.

I'm currently finishing up my Master's in CS at the University of Cambridge, with a focus on geometrically-inspired approaches to ML.I'm looking for ML Engineer/Dat Scientist jobs in NYC (where I lived and worked prior to my degree), but am open to remote jobs in the US generally (and am a US citizen so no visa requirements). Open to almost any industry, my number one criteria is working on interesting analytical and engineering problems!

My previous experience was as a data scientist at a hedge fund, working on leveraging alternative data to analyze private investment opportunities. I'm comfortable getting my hands dirty with messy datasets, building my own ETL pipelines, and working on challenging, ill-defined analytical problems that require creative solutions.

Technology-wise I'm best in python, including the usual DS stack (pandas/sklearn etc.), and am experienced with DL libraries (mainly PyTorch, some JAX/TF), and probabilistic programming/bayesian statistics libraries (PyMC3, BoTorch).