Watcherr is looking to hire a Data Scientist with a background in time series sensor data analysis, supervised and unsupervised machine learning and at least some background in Bayesian statistics or Bayesian probability.
About the role
- Computer science, applied mathematics or similar technical background (e.g. physics).
- Experience writing code for data applications. Python is essential (but they do not need to be at a super high level as a coder).
- Good understanding / knowledge of Bayesian statistics.
Would also be nice if you have…
- C/C++ proficiency.
- Proficiency with SQL and/or NoSQL databases.
- Time series statistical model analysis (e.g. ARMA/ARIMA and related).
- Machine learning time series analysis (for example Hidden Markov Models or Recurrent Neural Networks).
- Experience with modern deep learning techniques including transformer networks.
- Digital signal processing experience e.g. fourier transforms.
Please do not apply if you…
- Are a generic deep learning or machine learning person, although it would depend on what you have worked on in the past. E.g. image classification is a big part of deep learning but not very useful for this role.
- Have Natural Language Processing as your focus.
- Are a generic statistician.
- Are a pure mathematician, or an applied mathematician without coding experience.
How to apply
Please send your application, including your CV and a cover letter explaining a bit about yourself and why you’re suitable for this position, directly to email@example.com.