Senior Information Extraction Data Scientist

1 week ago

Laurel, Maryland, United States Johns Hopkins Applied Physics Laboratory (APL) Full time
Join Our Team as a Senior Information Extraction Data Scientist

We are seeking a highly skilled Senior Information Extraction Data Scientist to join our team at the Johns Hopkins University Applied Physics Laboratory (APL). As a key member of our Threat Analytics Systems Group (QAI), you will play a critical role in addressing complex information extraction challenges and developing innovative solutions for our national security challenges.

About the Role

As a Senior Information Extraction Data Scientist, you will be responsible for:

  • Conducting novel machine learning research to improve our ability to understand, represent, and reason about knowledge in text.
  • Communicating approaches, results, and impact to management, government sponsors, and the broader scientific community through papers, presentations, and technical reports.
  • Leading and collaborating on technical proposals to grow and define machine learning capabilities, including but not limited to NLP, information extraction, and knowledge representation.
  • Developing software to implement data science approaches.
  • Cultivating a long-term technical and research vision, collaborating with other researchers and experts to address challenges determined by sponsor requirements.
  • Designing creative AI/ML algorithms as well as developing analytic pipelines for analyzing large-scale, complex data.
  • Developing data architectures and pipelines to support analytic algorithms.
  • Collaborating with a multidisciplinary team to design, prototype, and develop ways to make ML models fast, performant, robust, and reliable under various data constraints.
  • Providing insight into the benefits and risks of proposed solutions to sponsor challenges, understanding and communicating not only how a problem could be solved, but how it can best be solved with given time, domain, or technical constraints.
Requirements

To be successful in this role, you will need:

  • A Doctorate degree in Computer Science, Applied Mathematics, Statistics, Engineering or relevant area.
  • Demonstrated ability to conduct machine learning research and develop production-ready software.
  • Proven ability in defining machine learning problems, particularly in NLP and knowledge representation, and identifying possible solutions given real-world constraints.
  • Proficiency with programming languages used in AI research (e.g., Python), and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch).
  • Experience proposing new ideas for research and development to stakeholders and potential sponsors.
  • Experience writing technical proposals or other forms of business development.
  • Experience with applications for national security or the intelligence community.
  • A track record of publishing research in scholarly journals or conferences (e.g., NIPS, IJCAI).
  • Experience with software engineering processes, techniques, and tools.
  • An active security clearance.
About APL

The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance.

All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law.

APL is committed to promoting an innovative environment that embraces diversity, encourages creativity, and supports inclusion of new ideas. In doing so, we are committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities.

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