Atmospheric Data Scientist

College Park, US-MD, US

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Position Description
ERT is seeking an atmospheric data scientist to support tasks at the Climate Prediction Center (CPC), part of the National Weather Service (NWS), National Centers for Environmental Prediction (NCEP), to improve seasonal forecast guidance by developing, testing, and implementing artificial intelligence (AI) and machine learning (ML) algorithms to consolidate dynamical and statistical model forecasts. Additionally, there will be focus on evaluating seasonal forecasts from a large ensemble set of dynamical model reforecasts.

Candidates must have demonstrated expertise in AI/ML and the applicability of various methods to predictions of weather or climate or other geophysical systems. It would be helpful to have an experience or deep understanding of methods to gain insight into the basis for the AI selections or results so it would not be a black box, such as through explainable AI, interpretability, causal discovery, etc. Candidates should be able to train, run, and verify AI/ML forecasts using typical meteorological parameters predicted by a large ensemble of dynamical models

Candidates also must have knowledge of weather and climate phenomena such as ENSO and familiarity with global forecast models and the output parameters and formats. Experience processing and analyzing atmospheric and/or other earth science datasets is essential.

Specific duties of the position include, but are not limited to

  • Evaluating reforecast model output of relevant variables from a large ensemble of seasonal forecasts, including verification techniques and use of verification packages such as METplus
  • Developing, training, and testing AI/ML methods for seasonal forecasting using inputs from statistical models and ensemble sets from several dynamical models
  • Comparing the skill of probabilistic tercile forecasts using the AI/ML model(s) to those of their input sources

Required Skills

  • Experience developing, training, and validating AI/ML models applied to geophysical or similar problems
  • Knowledge of a variety of AI/ML methodologies and their applicability to different problems
  • Experience utilizing large datasets in formats used in the atmospheric sciences such as GRIB/GRIB2, netCDF, etc.
  • Experience utilizing AI/ML packages and tools (e.g., keras, tensorflow, and/or others)
  • Ability to process and analyze statistical and dynamical model datasets including from ensembles of dynamical models and experience processing atmospheric or other earth-science data
  • Demonstrated proficiency in scientific programming languages such as Python, Fortran and in computational tools such as MATLAB or others
  • Experience working in a Linux environment
  • Knowledge of weather and/or climate phenomena and how they may influence a forecast
  • Candidates should be comfortable at fulfilling deadlines, working both independently and as part of a team within CPC working groups and projects, leading meetings and presenting results in a critical scientific environment, and communicating with stakeholders and academia through conferences and other mediums.

Must be a US Citizen or Permanent Resident who has lived in the United States at least 3 out of the last 5 years and be able to pass a background investigation to obtain a security badge to access applicable government facilities and systems.

Desired Skills

  • Familiarity with explainable AI, interpretability, causal discover, layer-wise relevant propagation, and/or other methods of allowing insight into the workings of the AI/ML models employed and the selections they make
  • Use of neural networks or other methods to separate forced climate signals from noise
  • Experience with probabilistic forecast verification methods
  • Experience with cloud computing
  • Demonstrated proficiency in shell scripting in Unix/Linux
  • Experience in a High-Performance Computing (HPC) environment

Education
Ph.D. in Atmospheric Science or Computer Science or related field 

Location
The position is eligible for up to 80% telework. Candidates must be able to work on site as needed at the National Center for Weather and Climate Prediction in College Park, MD, where they will work closely with scientists at both CPC and other NOAA agencies. 

Salary
The salary range for this role is $46,000 - 221,000/year. This range is a good faith estimate based on similar roles across the organization. ERT uses several factors when extending an offer, including but not limited to, the position's scope and expected duties, a candidate’s work experience, education/training, and key skills.  

Benefits
All full-time employees are eligible to participate in our flexible benefits package, which includes:

  • Medical, Rx, Dental, and Vision Insurance
  • 401(k) retirement plan with company-matching
  • 11 Paid Federal Government Holidays
  • Basic Life & Supplemental Life
  • Health Savings Account, Flexible Spending and Dependent Care Flexible Spending Accounts
  • Short-Term & Long-Term Disability
  • Employee assistance program (EAP)
  • Tuition Reimbursement, Personal Development & Learning Opportunities
  • Skills Development & Certifications
  • Professional Membership Reimbursement
  • Employee Referral Program
  • Competitive compensation plan
  • Discretionary variable incentive bonuses based on factors such as individual performance, business unit performance, and/or the company’s performance
  • Publication and Conference Presentation Awards with bonuses

ERT is a VEVRAA Federal Contractor and Equal Opportunity/Affirmative Action employer - All qualified applicants will be considered for employment without regard to race, color, religion, sex, national origin, disability, or protected Veteran status.

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Category: Data Science Jobs

Tags: Computer Science Fortran HPC Keras Linux Machine Learning Matlab ML models Python Security Shell scripting Statistics TensorFlow Testing

Perks/benefits: Career development Competitive pay Conferences Flex hours Flexible spending account Health care Insurance Salary bonus

Region: North America
Country: United States

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