teho98

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_UnJUniSSubk5H...

Email: [email protected]

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!

How does the compilation logic work? It’s described as optimizing the prompts just like you optimize the weights of a neural net, but what does that look like in practice?

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_UnJUniSSubk5H...

Email: [email protected]

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_UnJUniSSubk5H...

Email: [email protected]

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_UnJUniSSubk5H...

Email: [email protected]

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: [email protected]

Data Scientist and early-career ML researcher 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!

Does anyone know how Gröbner bases compare to homotopy continuation methods for solving systems of polynomials?

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.

Location: NYC Remote: Yes Willing to relocate: Yes Resume: https://docs.google.com/document/d/1ub1OP5yMZV_UnJUniSSubk5H... Email: [email protected]

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).

Location: NYC Remote: Yes Willing to relocate: Yes Resume: https://docs.google.com/document/d/e/2PACX-1vR0CGj68q0WKK32p... Email: [email protected]

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).

Location: NYC Remote: Yes Willing to relocate: Not immediately Resume: https://docs.google.com/document/d/e/2PACX-1vR0CGj68q0WKK32p... Email: [email protected]

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).