Data Scientist

Location: San Francisco, CA or Munich, Bavaria     Commitment: Full-time     Salary Range: $90,000 - $120,000 / year 

Description: Uncountable is seeking scientists and engineers who are passionate about statistics and technology. Our goal is to revolutionize industrial research and development with artificial intelligence.  We're looking for motivated data scientists who can help achieve this goal by helping our customers leverage our machine learning algorithms.

Primary Responsibility: Your primary responsibility will be to analyze our customers' data and configure our machine learning models to fit their projects.  You will serve as the statistics expert in calls with our customers and be responsible for maximizing the likelihood of success of their development effort.

This is a non-coding position. Our data scientists generally do not write code.

Requirements:
- Degree in Statistics, Chemical Engineering, Material Science, Physics or other STEM disciplines
- Expertise in statistical modeling and statistical theory
- Experience with high-dimensional modeling problems
- Interest in machine learning
- Communication ability and interest in speaking with our customers

Preferred Qualifications:
- Understanding of Bayesian statistics
- Experience with scientific experimentation and R&D

 

Example Interview Questions:
- Explain why it's convenient to assume linearity when modeling data.  What are problems with non-linear models?
- What are potential pitfalls of modeling sparse datasets?
- What does it mean for a model to be under-specified or over-specified?  How can you test whether either is occurring?
- You're mixing 4 ingredients such that the percent contribution of all the ingredients add up to 100%.  How would you design a trial with 20 experiments?

 

Important Clarification:
Uncountable is not a deep learning company nor a big data company.  Most of the problems we work with have fewer than 100 data points and almost all have fewer than 1000.
We take pride in our ability to be as accurate as possible with very little data.  If you're excited by very challenging statistics or optimization problems, this is the place for you.

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