Data Scientist

Silicon Valley, CA, United States

Datatron Technologies


Role Location

  • Silicon Valley, CA, United States

Employees

11 - 25 people

Address

5150 El Camino Real Ste C20
Los Altos, CA, 94022-1542, US

Tech Stack

  • Python
  • React
  • Containerization
  • TensorFlow
  • Scikit-Learn
  • Scala

Role Description

We are looking for a Data Scientist to apply data mining techniques, perform statistical analysis, and build high quality prediction systems integrated with the Datatron platform.

Responsibilities & Duties:

  • Selecting features, building and optimizing machine learning models
  • Data mining using state-of-the-art methods
  • Predictive analysis on large datasets

Skills & Qualifications:

  • Experience with building non-trivial machine learning models
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • Experience with open-source machine learning packages, such as Sci-kit Learn, Weka, etc.
  • Experience with at least one object-oriented, scripting language (Python, Java/Scala, Ruby, Perl)
  • Proficiency in using query languages such as SQL, Hive or Pig
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.

Good To Haves:

  • Degree in Computer Science or Data Science
  • Experience building deep learning models using open-source frameworks e.g. Tensorflow, Keras, Pytorch
  • Experience with data visualisation tools, such as Matplotlib, Plot.ly, D3.js, GGplot, etc.
  • Experience deploying machine learning models in production

About Datatron Technologies

Datatron speeds up the AI life cycle model-management in today’s machine-learning paradigm by orders of magnitude. We deploy ML model deployment, scoring, monitoring, and model governance to enterprise clients in the financial, healthcare, and telecommunication sectors.

Company Culture

We are looking for talented individuals who are eager to learn, want to interact with customers and want to have a chance to make a big impact.

Interested in this role?
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