Data Science Section Supervisor
- Johns Hopkins Applied Physics Lab
- Location: Laurel, Maryland
- Category: Science-Other
- Posting Date: 09/11/2019
- Application Deadline: Open until filled
Data Science Section Supervisor - A3G-6-21943
Are you passionate about solving technical challenges in rapidly growing and evolving data science, machine learning, and artificial intelligence fields?
Do you find developing and inspiring individuals to reach their maximum potential rewarding?
If so, we're looking for someone like you to join our team at APL.
The A3G-6 Section Supervisor will lead A3G-6 and assist the A3G Group Supervisor in leading our group of savvy scientists and engineers focused on developing advanced technologies and algorithms in support of the Air and Missile Defense mission. We are looking for a tried-and-true leader and domain expert who can offer technical contributions to projects that employ advanced data science, machine learning, and artificial intelligence techniques to solve critical AMDS problems.
As a Data Science Section Supervisor...
· You will contribute significantly to the evolution and implementation of the A3G group vision, strategy, and execution (VSE) plan where the activities of your section staff provide part of a foundation for that VSE. Propose research initiatives and implement inspiring strategies to address current and future challenges facing air and missile defense. Set a clear vision and path for the section and prioritize section needs.
· You will recognize data science and machine learning needs, work with supervisors/task leaders to evaluate the needs of their respective process, and figure out the type of data science tasks required. Assemble a team of relevant subject matter experts and employ the best tools and methods to answer the sponsors’ questions. Interface heavily with sponsors and management both within and outside of APL. Analyze data science results and information to draw robust inferences about pertinent phenomena and their consequences on combat system behavior and performance. Compile technically solid conclusions and communicate clear recommendations to the sponsor.
· You will actively engage and partner with section staff to assess their strengths and their limitations. Work with staff to understand their career objectives and seek to match staff development with project objectives. Mentor and coach staff members. Provide and guide staff development opportunities, including participation in the annual performance coaching process.
· You will assess the section’s current and future work and define and propose the analytical and physical infrastructure necessary to carry out that work. This may include suggesting new improvements to facilities, computing resources, tools, laboratories, work spaces, etc. Assist with the annual capital and task planning processes.
· You will provide supervision and staff planning, including monitoring technical work for accuracy and quality. Delegate and assign task assignments to team members and efficiently execute individual responsibilities. Assist the group supervisor in the interviewing and hiring processes. Assist with, and implement, staff development initiatives, including staff mentoring, onboarding, and working with staff to understand their career objectives. Support the section and its staff members by implementing AMDS and Laboratory policies and procedures.
You meet our minimum qualifications for the job if you...
· Possess a Master's degree in computer science, mathematics, electrical engineering or other relevant field
· Have 5+ years of experience or equivalent combination of education and experience
· Have a strong technical background in data science, machine learning, and/or artificial intelligence algorithms, as well as previous experience in crafting and implementing machine learning algorithms for a variety of datasets
· Have experience in typical data science packages such as: Pandas, Tensorflow, skleam, and/or matplotlib
· Have a confirmed history of successful and critical contributions to DoD sponsors on projects related to the implementation of robust analytical concepts and algorithms
· Have demonstrated strength in verbal communication skills, including experience with technical briefings to project sponsors
· Have excellent writing skills, including experience writing technical memoranda or journal articles
· Have staff development and/or mentorship experience
· Possess strong technical leadership skills
· Have the ability to obtain a Top Secret clearance. Candidate must possess a final Secret clearance on start date. Applicant selected 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 a PhD in computer science, mathematics, electrical engineering, or equivalent
· Have 7+ years of relevant experience or equivalent combination of experience and education
· Have previous line management experience
· Have demonstrated successful business development skills by working with the program office
· Have experience giving peer-reviewed conference presentations
· Have a demonstrated understanding of the BMDS or Navy domains
· Possess an active Top Secret clearance
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. With a wide selection of challenging, impactful work and a robust education assistance program, APL promotes a culture of life-long learning. Our employees enjoy generous benefits and healthy work/life balance. APL’s campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at www.jhuapl.edu/careers.
APL is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability status, veteran status, or any other characteristic protected by applicable law.
Primary Location*United States-*Maryland-*Laurel