Lead Data Scientist for Data Analytics
Lead Data Scientist for Data Analytics
Are you ready to apply your expertise and unique leadership in data science on data analytics and uncertainty quantification to answer profound questions of the universe and the challenges of robotic space exploration?
JPL is seeking a Lead Data Scientist for Data Analytics and Uncertainty Quantification to advance data science theory and practice across the JPL mission lifecycle from mission formulation to science data analysis.
The Jet Propulsion Laboratory (JPL) of the California Institute of Technology is a leading national laboratory supporting NASA Planetary, Earth, and Astrophysics missions, combining renowned expertise in technology, engineering, and science. JPL is at the forefront of instrument development, mission architecture design, robotic technology development, autonomy, and remote-sensing advances in space and Earth sciences. Meeting future challenges in these areas requires making significant advances in a number of data science areas, including scalable and traceable approaches to data analysis, synergistic use of observations and complex models, uncertainty quantification, and data-driven modeling.
You will facilitate advancement of the Data Science community at JPL developing a unified vision and coherent approach across areas of science discovery, integration of measurement and model data, and increasing effectiveness of measurements and operations through data science technologies. The generation of observational, model, and engineering data is anticipated to outpace the capacity of current analysis methods. Novel, scalable, systematic approaches are needed for both data-analytic techniques and computing infrastructures to handle these massive, distributed, heterogeneous data sets. In addition to this big data problem, new challenges have arisen in supporting scientific inference, decision-making, and data/model integration, that demand probabilistic uncertainty assessment and measurement traceability. JPL is familiar with management and pipeline processing of large data volumes, but sees a future where the Lab is a world leader in exploiting these data to make robust scientific discoveries, with well-supported statistical significance, from massive volumes of multi-faceted data sources.
You will facilitate a community of practitioners across JPL's data science activities to make an impact on JPL mission formulation, operation, and scientific analysis.
To help set the Laboratory's direction with respect to advancing data science, we seek candidates who have demonstrated accomplishments and leadership in solving practical data science challenges with observational science data, physical model outputs, and engineering data, and in conducting novel and integrative research.
Candidates should also have the following qualifications:
- A strong emphasis on uncertainty quantification and data-driven modeling is highly desirable.
- A proven track record conducting applied and theoretical research, collaborating with researchers in a variety of application domains, and leading sustained cross-disciplinary development efforts.
- Significant experience leading diverse teams enabling transformational innovations.
- Internationally recognized researcher in data analysis techniques and methods applicable to a wide variety of applications and domains.
- Extensive experience forming and leading multidisciplinary, cross-organizational teams.
- Ph.D in Computer Science, Statistics, Mathematics, Machine Learning or related technical discipline with a minimum of 8 years of relevant experience, or a Master's degree with 10 years of related experience or a Bachelor's with 12 years of related experience.
Caltech/JPL is an Equal Employment Opportunity (EEO) and affirmative action employer. It is the policy of Caltech/JPL to provide equal employment opportunities, actively recruit, and include for employment consideration all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
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