Picarro

Data Scientist

Santa Clara, CA, US$130,000-$150,000Posted 12 days ago

Job Description

Data Scientist

Job Location: Santa Clara, CA (preferred) or Remote – US-based

Job Term: Full-Time

The Opportunity

Picarro's instruments and analytics power industrial emissions detection, from methane and VOC leak detection to process and emissions monitoring at industrial facilities. We're looking for a Data Scientist who can apply rigorous statistical and physical modeling to Picarro's core measurement challenges: detecting, attributing, localizing, and quantifying trace gases and emissions from complex sensor data.

You'll work closely with the data analytics, customer success, product, and engineering teams, applying and extending broadband spectroscopic analysis techniques and translating that understanding into models and algorithms that directly shape our products and solutions.

What You'll Do

  • Develop and implement models and algorithms for the detection, attribution, localization, and quantification of trace gases and emissions across measurement platforms and applications.
  • Build models of atmospheric transport and dispersion (e.g., Gaussian plume, WRF, HYSPLIT), or work closely with those who do, to support emissions analytics in diverse settings, including industrial facilities, pipelines, and urban and natural environments.
  • Apply statistical techniques such as Bayesian inference, hypothesis testing, and Monte Carlo simulation to quantify uncertainty and improve the interpretability of results.
  • Work with time-series and geospatial data to build analytical workflows that combine sensor data with atmospheric and geospatial context.
  • Design and run experimental programs to develop and validate algorithms, deepening our understanding of plume propagation and detection.
  • Write both experimental and production code and translate research-stage models into components engineering can integrate into Picarro's production cloud platform.
  • Use modern AI-assisted coding tools as part of the day-to-day workflow

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