Data Scientist - Measurement & Inference

Job Description

Posted on: 
April 6, 2023

As a Data Scientist (measurement & inference) you will ensure that AI outputs fit customer preferences at granular scale via segmentation, experimentation, and developing models which anticipate and prioritize customer behavior.

Our target market is composed of content creators and marketing leaders at growing companies. We help companies leverage artificial intelligence to accelerate content production and unlock their best ideas. We see AI as a partner to content marketers that can help them break through writer’s block, create fine-tuned imagery, and repackage content for different formats, languages and tones.


  • Develop state of the art user segmentation and clustering, design and execute causal inference strategies employed now and in the future, set the strategic roadmap for intervention optimization beyond A/B experiments (bandits, etc.)
  • Research measures of customer acceptance on generated output using state of the art large language models to extract semantic meaning, segmentation, clusters, and gauge quality and complexity.  
  • Own the experimentation roadmap for the data org, work with leadership to build strategic confidence in the experimentation framework, define what success looks like for the product roadmap.
  • Implement large scale ETLs on metrics and measurements you develop to track, correlate to long term business outcomes, and work with partner teams to move them through experimentation.
  • Test hypotheses and implement findings about how to improve user experience with the models that power our product. Once validated, working to implement findings as AI product modifications which increase customer delight or scale. Findings may also be used to advise our research partners or product managers on new directions

Job Requirements

  • Experience getting AI/ML to value, including NLG and feature engineering. Experience with text, image, and other R&D communities is a plus (~2 years per level)
  • Commitment to rigorous A/B testing and causal inference, as well as an interest in user experience and behavior, and trust and safety
  • A willingness to be technique, method, and tool agnostic and systematically turn any knob that might improve customer outcomes
  • Strong knowledge of frameworks such as TensorFlow, PyTorch, Keras
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