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Evolver

Research Scientist - Information Theory and Statistical Inference

Evolver · Palo Alto, California

Posted 6 days ago

or apply directly on Evolver's site. We never take the application ourselves.

Is this posting real?

This role has been open
6 days
Evolver's roles stay open a median of 45 days
Reposted
No
Salary listed
No
0% of Evolver's roles list one
Ghost-job risk at Evolver
high
11 stale, 0 reposted of 20 open
Hiring momentum
22 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-09-17

Measured from postings appearing on and disappearing from Evolver's own greenhouse board since 2026-08-03. Full hiring picture for Evolver.

About this role

As a Research Scientist at Evolver, you will focus on developing methodologies to transform large-scale enterprise data into decision-relevant information. Your work will involve applying information theory and statistical inference to quantify information content and uncertainty, as well as building algorithms and prototypes for information-aware AI systems. Collaboration with research, engineering, and product teams will be essential to translate your methodologies into practical applications.

Our read on this posting2.8out of 5
benefits
1/5
freshness
5/5
career value
4/5
role clarity
4/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Evolver as an employer.

What you need

  • Ph.D. or thesis-based Master's degree in a quantitative field
  • Strong mathematical foundation in probability, statistics, information theory, or statistical inference
  • Research experience in information theory, Bayesian or statistical inference, uncertainty quantification, or related areas
  • Strong Python, MATLAB, or equivalent scientific computing skills
  • Ability to translate mathematical concepts into computational methods and working prototypes

Nice to have

  • Experience with information bottleneck methods, sufficient statistics, or rate-distortion theory
  • Experience working with large-scale, noisy, heterogeneous, or partially observed data
  • Research publications or demonstrated research impact
  • Experience connecting theoretical methods to real-world data or decision-making problems
  • Familiarity with modern machine learning or representation learning

Worth weighing

  • No salary listed
  • Focus on mathematical depth and research ability over years of experience may appeal to recent graduates
  • The role involves collaboration across teams, which may require strong communication skills

Summarised from Evolver's posting. Read the full original.

Listed by Evolver on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.

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