Infusion Data Scientist

  • Green Job Crawler
  • Virtual, USA
  • 27 Apr, 2020

Job Description

Do you excel in an environment that values exploration and discovery? We have a universe of opportunities waiting for you! The Jet Propulsion Laboratory (JPL) is NASA’s lead center for robotic exploration of the solar system. Our core competency is the end-to-end implementation of unprecedented robotic space missions to study Earth, the Solar System, and the Universe. The Instrument Software and Science Data Systems (Org. 398) Section within JPL consists of multidisciplinary teams of engineers and technologists who provide expertise across the domains of instrument operations and science data systems. We are responsible for: + Safely controlling JPL remote sensing instruments + Transforming instrument data into scientific measurements and preserving them for future analyses + Providing context and understanding to the measurements + Making these results accessible to the global community: scientists, operations, decision makers and society Our engineering teams build and operate high performance data processing, management and analysis systems capable of handling petabyte scale datasets in support of science discovery, research, operations and applications. They support JPL and NASA missions, as well as other science-based projects. Our research and technology development teams create new onboard and ground based technologies for data processing, analysis, modeling, reasoning, visualization, management, access and analytics that are infused into our data systems. JPL, located in Pasadena, California, has a casual, campus-like environment situated on 177 acres in the foothills of the San Gabriel Mountains and offers a work environment unlike any other: we inspire passion, foster innovation, build collaboration, and reward excellence. We are proud to be part of NASA and Caltech, as we explore the universe and make history through new discoveries. We aim to do things never done before and to go places few can go. We dare mighty things…do you? The Machine Learning & Instrument Autonomy Group (MLIA) The new research data scientist will be a member of MLIA, with both recently graduated and experienced candidates welcome. We employ rigorous, explainable Machine Learning (ML) methods to support science-enabling data investigation on the ground, inform spacecraft operations teams in a time-critical setting, infuse new capabilities into JPL’s space missions, and extend the reach of scientists beyond Earth by creating autonomous “smart” instruments that can recognize and prioritize discoveries. We eschew “black box” ML, and often our trained models are created and examined explicitly to shed light on complex data and increase human insight rather than to automate a process. We collaborate with scientists, spacecraft operators, and engineers to identify novel ways that ML and data-driven science can help achieve their goals. Finally, we infuse ML solutions throughout JPL and NASA to bring about a richer, deeper, and more complete understanding of our universe from the Earth to the stars. We measure the success of our applied ML systems in terms of human hours saved, additional discoveries made, or new questions that may be addressed. We also frequently act as ambassadors to science and engineering areas not yet familiar with data-driven approaches by teaching, explaining, and aiding those ready to receive it in the complex and often risk/change-averse arena of space exploration. Specific Job Responsibilities: The infusion data scientist will: + Implement algorithms and data processing methods for airborne and satellite remote sensing platforms and planetary surface missions as re-usable, generalized systems to open-source standards + Collaborate with domain experts from a variety of natural science fields, operations staff, and ML researchers + Support publication via peer-reviewed conferences, workshops, and journal papers + Assist in obtaining funding through competitive grant proposals + Proactively identify new use-cases in Ops and formulate proposals for relevant new data-driven capabilities + Bachelor’s degree in Electrical Engineering, Computer Science, or related technical discipline with typically 1 year of related experience; Master’s degree in similar disciplines with a minimum of 0 years of related experience + Minimum 3.0 GPA + Thorough proficiency in Python including NumPy, SciPy, Pandas, and Matplotlib + Demonstrated modern software engineering skills, unit testing, functional testing, continuous integration (Jenkins), configuration management, Github + Demonstrated ability to work with ML research staff and infusion end users (instrument operators, science data system operators, Mission staff, Mission scientists) + Demonstrated experience implementing maintainable and reusable software for scientific applications + Strong written and oral communication skills including data visualization, presentation, and explanation of software design, research results, user guidance, and project status + Love of implementation and desire to grow career in implementation/infusion support for novel ML products + Team-building mentality, can-do attitude, and commitment to project success + Patience to educate researchers in modern software standards and determine appropriate project rigor + Very high productivity with project-level, strategic guidance onlySignificant programming experience with C/C++ + Familiarity with applied probability and statistics, linear algebra, and numeric optimization + Interest in science data processing, uplink/downlink processes, and instrument modeling + Experience analyzing complex datasets for artifacts, known signals, and anomalous contents + Cloud, cluster, and multi-core parallelization paradigms + A love of space, exploration, and science Posted Title: Infusion Data Scientist Requisition ID: 2020-11811 Discipline Description: Data Science Career Level: Level 1 Relocation Eligibility: No Name: 398J - MACHINE LEARNING AND INSTRUMENT AUTONOMY Work Authorization: U.S. Citizen or Permanent Resident Clearance Status: None External Company URL: Post End Date: 4/27/2020 Telecommute: Yes