The data science candidate is responsible for the collecting, cleaning and munging of data in ways to determine the value of the data and extract that value for discovery and decision support. Our data scientist are part detectives and business analysis. The detective work comes in handy when parsing, clustering, and stratifying the data to find and amplify signals in the data. The business analysis is used to determine what signals they should look for based their understanding of the client’s business goals for collecting the data.
The candidate will be responsible for handling the extract, transform, and load (ETL) for multi-domain data. They will be applying various machine learning algorithms to the multi-domain data to measure the performance of the algorithm and the suitability of the data. The candidates first set of algorithms will be for homomorphic encryption (HE). With those algorithms, the candidate will be experimenting with ways to increase the speed of homomorphic encryptions by orders of magnitude. The candidate must be a self-starter and honestly self-assessing to know when to seek assistance. Also, the position requires a candidate who can communicate well and able to present their work to internal and external groups.
- Bachelor's degree in Computer Science, Data Science or related field and 2-4 years of relevant experience or Masters with less than 2 years experience.
- Good understanding of machine learning algorithms, tools and platforms
- Experience in at least one of these Toolkits: numpy, scipy, scikit-learn, tensorflow, pytorch, keras, genism, vowpal wabbit, etc.
- Understanding of programming fundamentals
- Python proficiency
- Self-starter and intellectual curiosity
- Great communication skills, ability to explain predictive analytics to non-technical audience
- Proficiency in data exploration techniques and tools
- Must be able to obtain TS/SCI with CI Poly security clearance.
- Experience programming machine learning algorithms for GPUs
- Understanding of Convolutional Neural Nets
- Working knowledge of Keras
- Discernment of when and how to use machine learning regulation
External Referral Bonus:Ineligible
Potential for Telework:Yes, 50%
Clearance Level Required:None
Travel:Yes, 10% of the time
Scheduled Weekly Hours:40
Job Family:Data Scientist
Leidos is a Fortune 500® information technology, engineering, and science solutions and services leader working to solve the world’s toughest challenges in the defense, intelligence, homeland security, civil, and health markets. The company’s 38,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Va., Leidos reported annual revenues of approximately $11.09 billion for the fiscal year ended January 3, 2020. For more information, visit www.Leidos.com.
Pay and Benefits
Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available here.
Securing Your Data
Leidos will never ask you to provide payment-related information at any part of the employment application process. And Leidos will communicate with you only through emails that are sent from a Leidos.com email address. If you receive an email purporting to be from Leidos that asks for payment-related information or any other personal information, please report the email to [email protected].
Commitment to Diversity
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.