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Remote Applied Scientist jobs

15 open positions in the United States, newest first.

Applied scientists use machine learning and statistics research to solve concrete product problems, such as ranking, recommendation, forecasting or language understanding. The role sits between research scientist and ML engineer: they design models and experiments with scientific rigor and are also expected to get the result into production. They are accountable for measurable improvement, not publications alone.

About the Applied Scientist role

What the work looks like

  • Frame a business problem as a modeling problem, choosing the objective, data and evaluation metrics.
  • Train and evaluate models in PyTorch or similar frameworks, comparing against baselines with offline experiments.
  • Read current research papers and adapt promising methods to the company's data and constraints.
  • Design online A/B tests with engineers and analyze whether a model change truly moved the metric.
  • Write production-quality code or work closely with ML engineers to deploy and monitor the model.

What employers ask for

  • MS or PhD in a quantitative field
  • Python with PyTorch or TensorFlow
  • Machine learning theory and statistics
  • Experiment design and A/B test analysis
  • SQL and large-scale data processing with Spark
  • Publication record valued at some employers

Doing this job remotely

Modeling work happens on remote compute clusters anyway, so location matters little for the technical side. Research benefits from frequent informal discussion, and remote scientists need to create that deliberately through reading groups and written proposals. Access to sensitive training data can restrict where and on what hardware the work is done.

Where it comes from and where it leads

Applied scientists usually enter from a graduate program in machine learning, statistics or a related science, or move over from data science or ML engineering. They advance to senior and principal applied scientist, or into research management.