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Senior GNSS Data Analyst and Team Lead R17250

Please note: In order to be considered for this position, you must apply directly via the Workday website. 

https://utaustin.wd1.myworkdayjobs.com/UTstaff/job/PICKLE-RESEARCH-CAMPUS/Senior-GNSS-Data-Analyst-and-Team-Lead_R_00017250-1

Job Details:

Responsibilities


  • Hire, mentor, train, and evaluate performance of data analysts
  • Perform analysis, statistical characterization, and interpretation of GNSS observation data and broadcast navigation message data.
  • Design, develop, test, and deploy software for GNSS data analysis, automated reporting, and data processing pipelines.
  • Communication of work process, products, and results, including code documentation, written reports, and briefs presented to stakeholders.
  • Collaboration and coordination of work and planning across multiple teams for analysis, software development, documentation, and reporting.
  • Other related functions as assigned.


Required Qualifications


  • Bachelor's degree in physics, astronomy, statistics, computer science, computational science, or related discipline with strong emphasis on statistics and software development.
  • Three or more years relevant professional work experience in data analysis, data engineering, or data science, with an emphasis on analysis software development.
  • Demonstrated ability to design, develop, analyze, test, debug, deploy, maintain, deploy, and support large and complex source code libraries.
  • Demonstrated proficiency in using analysis software, statistics, scientific computing, and data visualization to produce actionable insights from data.
  • Strong verbal and written communication skills, including demonstrated ability to communicate technical detail to staff and stakeholders of varying backgrounds and experiences.
  • Demonstrated ability to work effectively, both independently and collaboratively, with a strong commitment to contribution and enabling the entire team.
  • Demonstrated ability to mentor or lead more junior personnel and students.
  • Possess high degree of emotional intelligence.
Applicant must have a dynamic skill set, willing to work with new technologies, be highly organized and capable of planning and coordinating multiple tasks and managing their time. The position will require attention to detail, effective problem solving skills and excellent judgment. Ability to work independently with sensitive and confidential information, maintain a professional demeanor, work as a team member without daily supervision and effectively communicate with diverse groups of clients. Able to work under pressure and accept supervision. Regular and punctual attendance.
US Citizen. Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information at the level appropriate to the project requirements of the position.


Preferred Qualifications

Strong candidates for this position will have engaged in specialized study or research in the areas of GNSS systems and/or GNSS signal structures, data science, time-series analysis, and scientific computing for at least 5 years, and have demonstrated working knowledge applying C/C++, Cython, Julia or R; and experience with the scientific Python stack including NumPy, SciPy, pandas, statsmodels, Matplotlib, and/or Jupyter. Five or more years experience in data analysis focusing on feature detection, modeling, and forecasting is a plus.
While not required, working knowledge of Agile techniques, DevOps, data engineering, and automation tools such as bash, make, dask, pip, conda, Docker, and Slurm would be of benefit, along with experience of revision control and collaboration tools such as git, GitLab, GitHub, and Jira.


General Notes

An agency designated by the federal government handles the investigation as to the requirement for eligibility for access to classified information. Factors considered during this investigation include but are not limited to allegiance to the United States, foreign influence, foreign preference, criminal conduct, security violations, drug involvement, the likelihood of continuation of such conduct, etc.
Please mark "yes" on the application question that asks if additional materials are required. Failure to attach all additional materials listed below may result in a delay in application processing.
Please visit our website (www.arlut.utexas.edu) for additional information about Applied Research Laboratories.