Note: The job is a remote job and is open to candidates in USA. Picarro develops instruments and analytics for industrial emissions detection, including methane and VOC leak detection and process monitoring. The Data Scientist will develop statistical and physical models for detecting, attributing, localizing, and quantifying trace gases and emissions, while translating research-stage algorithms into production solutions. The role also involves working with sensor, atmospheric, time-series, and geospatial data and communicating findings to technical and non-technical stakeholders.
Responsibilities
- 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, alongside good engineering practices
- Manage, process, and visualize large, complex scientific datasets to extract actionable insight for internal and external stakeholders
- Maintain rigorous documentation and communicate findings clearly to both technical and non-technical audiences
Skills
- Ph.D. or Master's in Physics, Applied Math, Atmospheric or Ocean Science, Astrophysics, Engineering, or a related physical science, or equivalent applied experience
- 2+ years of related research or industry experience (postdoctoral research counts)
- Strong foundation in statistical modeling, including Bayesian methods and uncertainty quantification
- Hands-on experience with time-series and geospatial data
- Proficiency in Python for numerical analysis (Pandas, NumPy, SciPy, Matplotlib, etc.) and SQL
- Goal-oriented with strong organizational skills and the ability to manage competing priorities with minimal supervision
- Strong technical communication skills, able to translate complex analysis for both scientific and non-technical audiences
- Exposure to atmospheric transport and dispersion concepts (e.g., Gaussian plume models, WRF, HYSPLIT) is a plus; we're happy to build this depth on the job for someone with a strong physical modeling and statistics foundation
- Familiarity with cloud computing environments (AWS preferred) and software development best practices (version control, code review, testing) is a plus; candidates without this should expect to develop it on the job
Benefits
- Medical, Dental, and Vision insurance
- Flexible Spending Account (FSA) and Health Savings Account (HSA) plans
- Life, Short-Term Disability, and Long-Term Disability Insurance
- Paid Time Off and Paid Holidays
- Employee Referral Program
- 401K
- Social events (summer picnic, holiday party, team lunches, etc.)
- On-site Health & Wellness programs (fitness challenges, outdoor bootcamp, flu-shots, etc.)
Company Overview
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