26 days old

Software Engineer – Data Science & Machine Learning

Lynker Technologies
Tuscaloosa, Alabama
  • Job Type
  • Job Status
    Full Time

Software Engineer – Data Science & Machine Learning

Position 2017958669 – Software Engineer – Data Science & Machine Learning

Job Description:

Lynker Technologies, LLC has an exciting opportunity for a Software Engineer – Data Science & Machine Learning at the National Water Center. This position is ideal for a data science and machine learning enthusiast with a sense of ambition and passion to work in the water and environment sciences with the focus on water resources management.

The NOAA National Water Model (NWM) provides operational analyses and assessments of the full range of water cycle components across the United States, with an emphasis on streamflow. Accurate simulation of these elements entails proper representation of all relevant physical processes and anthropogenic influences that impact the flow of water. Reservoirs are operated in ways that are governed by a mixture of natural forcing and water law. Reservoirs can be operated for flood control, water supply, energy production, and water storage purposes, with each purpose having unique governing requirements. Over 1,000 reservoirs are currently represented in the NWM, with more expected in subsequent model releases. However, the current representation is rudimentary. Enhancements to this representation in the NWM will need to take into account the wide variety of factors that influence operations over the course of each water year.

A majority of reservoirs do not have clear operating rules, requiring a different approach to represent their contribution to the NWM. This position will work on ML approaches for doing this. From pre-processing large amounts of data from various resources to coding and testing  various models, this position presents a unique opportunity to apply data science and machine learning. NOAA believes such techniques have the potential to intelligently integrate a wide variety of factors to model reservoir operations within the NWM.

Responsibilities include implementing a ML model that will replicate the behavior of reservoir managers in order to accurately simulate reservoir releases within the NWM framework, including:

  • Working with a hydrology expert to design, construct, integrate and test new NWM modules.

  • Developing preprocessing pipelines for applicable data.

  • Designing interfaces necessary to enhance NWM capability.

  • Assist in integrating the code into the current version of the NWM.

  • Develop documentation and code to accomplish the reservoir modeling improvements outlined above.

  • Communicating model and testing results (verbally and/or graphically with diverse audiences.)

  • Continuous learning of state of the art techniques.  Includes reading scientific papers and technical documents related to both machine learning and water resources.


Required Qualifications:

  • BS degree* in Computer Science with applicable coursework and/or projects related to data science and machine learning.

  • Must have a collaborative nature and willing to work with Earth Scientists and other Software Engineers (comprised of a mix of employees and consultants) onsite.

  • Background in data processing, data mining, time series analysis, and/or predictive models in Python (familiarity with Python toolboxes are strongly recommended: SciPy, NumPy, Pandas)

  • Python experience is required along with experience with one or more of the following: FORTRAN, MATLAB, C, C++, Java Scala, Lua, or any other proficient AI language

*Degree preferred, but not required if candidate possesses equivalent applied data science and machine learning experience and expertise.

Desired Qualifications:

  • MS with 5+ years in Computer Science field, or PhD with 2+ years in Computer Science field, or BS with 8+ years of applied machine learning experience

  • Strong background in Machine Learning (ML) techniques, development and applications in Python (Keras, Theano, Tensorflow, Caffe, MXNet, SciKit-Learn)

  • Strong background in mathematical, statistical and probability concepts/methods

  • Ability to “stay ahead of the game” by knowing what is and will be state of the art in machine learning as well as applications in hydrology and water resources.

  • Applicants must have US residency

This position is based at NOAA/OWP National Water Center, located in Tuscaloosa, AL.


  • Data Analytics
  • Data Engineer
  • Data Scientist

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Software Engineer – Data Science & Machine Learning

Lynker Technologies
Tuscaloosa, Alabama

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Lynker Technologies
Tuscaloosa, Alabama

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