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Data Scientist

$100k

The Johns Hopkins University Applied Physics Laboratory

Description Are you passionate about building solutions for our greatest national security challenges? Are you searching for engaging work with an employer that prioritizes impact, innovation, and personal development? Do you value working in a creative and collaborative environment? If so, we're looking for someone like you to join our team at APL. The Threat Analytic Systems (QAI) Group is seeking engineers, scientists, and developers with a curiosity and drive for learning who can translate advanced technologies into mission impact. At APL we make critical contributions to our nation's critical challenges, and we do so in a collaborative and dynamic environment that cultivates curiosity, innovation, and creativity. We are looking for candidates with strong fundamentals and the ability to learn quickly in a dynamic mission space. As a member of our team, you will... Develop, evaluate, and improve technical approaches to challenging, non-routine problems involving artificial intelligence / machine learning (AI/ML), data science, and related technologies Design and contribute to prototype software that gathers, processes, and analyzes data from sources ranging from the open web to authoritative ontologies and knowledge graphs Research, explore, and develop innovative techniques and technologies in the field of artificial intelligence Assess the strengths, limitations, and tradeoffs of technical approaches and help teammates and sponsors understand how to improve, extend, or adapt them to new problems Communicate ideas, methods, and results clearly through papers, presentations, and discussions with technical staff, leadership, and government decision makers Qualifications You'll meet our minimum requirements if you have... BS or BA in Computer Science, Mathematics, Physics, Computer Engineering, Electrical Engineering or related field Experience applying AI/ML, natural language processing (NLP), statistical analysis, or related technical fields to real-world problems Experience developing reliable software (Python preferred), with the ability to contribute to shared code bases using sound software-engineering practices Comfort working from loosely defined or high-level requirements Strong problem solving, analytical, and organizational skills Ability to manage priorities across multiple dynamic projects supporting evolving national security needs Demonstrated initiative and ability to work effectively both independently and as part of a team Strong written and verbal communication skills, including the ability to explain technical ideas to audiences with varied technical backgrounds Have the ability to obtain a TS/SCI level security clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship. You'll go above and beyond our minimum requirements if you have... MS or PhD in Computer Science, Mathematics, Physics, Computer Engineering, Electrical Engineering, or related engineering field Experience designing and developing AI/ML approaches for interdisciplinary problems Experience architecting, implementing, and testing prototype software intended for sustained use by a team Experience communicating technical findings and recommendations to sponsors, leadership, or other decision makers About Us Why Work at 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. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates. At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at 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 providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please View email address on click.appcast.io. The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis. Minimum Rate $100,000 Annually Maximum Rate $245,000 Annually The Johns Hopkins University Applied Physics Laboratory

Vacancy posted 3 days ago
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