Junior Data Science Engineer ( R-00084261-OTHLOC-PL-2D2504 )
The Defense Group at Leidos has an opening for a Junior Data Science Engineer for the Global Solutions Management – Operations II (GSM-O II) contract. This contract includes the Operations, Sustainment, Maintenance, Repair and Defense of the Defense Information System Network (DISN) within the DOD Information Network (DODIN) in support of the Defense Information Systems Agency (DISA). This role is primarily remote, but candidates must be within commuting distance to Scott AFB, IL or Ft. Meade, MD or Ogden, UT for on-site support.
Solve stakeholder problems and improve business efficiency through direct quantitative and qualitative data analysis, followed by the design, implementation, and documentation of the solutions as repeatable processes.
Obtain and integrate data sets from disparate technical environments to support network, performance, application and configuration use cases, performing extraction, transform, and load (ETL) tasks and developing ETL pipelines.
Develop, test, and maintain data models (both physical and logical), including identifying the data’s relevant metadata to ensure consistency, quality, accuracy, integrity, information assurance, and security.
Leverage AI/ML techniques, including supervised and unsupervised learning, to increase efficiencies by creating and optimizing data pipelines that support predictive analytics, classification, anomaly detection, and decision tree use cases.
Develop, train and deploy AI/ML models using resources and tools in an AWS containerized environment.
Configure and prototype ML solutions in Jupyter notebooks.
Work collaboratively with a cross-functional, geographically dispersed team and partner closely with Network Operations stakeholders to develop data analytics automation techniques to improve results and efficiency.
B.S. degree in Aerospace Engineering, Computer Science, Mathematics, Statistics, Physics, Electrical Engineering, Computer Engineering, Data Science, or Data Analytics and 1+ year of related experience obtained through any combination of coursework and internships.
Educational experience or courses/projects in Artificial Intelligence, Machine Learning and Statistics.
Practical experience with Machine Learning, Natural Language Processing, and/or Artificial Intelligence and the ability to apply these techniques concrete problems.
Practical hands-on data experience, including the ability to hypothesize, test and explain statistical analysis techniques that can be applied to the data to provide business value.
Strong communication skills that will enable proactive and effective collaboration with a virtual team of data engineers and DevOps engineers, including the ability to articulate data requirements and translate requirements from stakeholders for AI/ML project needs.
Experience in R, Java, Python, Scala, SAS, SPSS or similar.
Experience following a software development lifecycle, including developing and maintaining production quality code.
Ability to obtain interim Secret DoD Security clearance prior to start date.
Ability to obtain Security+ certification or equivalent DoD 8570 IAT II certification within 60 days of start date.
Experience developing data analysis prototypes.
Practical experience applying data analytics to business problems.
Experience automating data cleansing, formatting, staging, and transformation.
Experience with text mining tools and techniques, including in areas of summarization, search (e.g., ELK Stack), entity extraction, training set generation, and anomaly detection.
Familiarity with CI/CD techniques to develop and release software using containerized pipelines.
Experience with Big Data tools including Elasticsearch, Logstash and Kibana, Apache Kafka, NiFi, Apache Spark, Neo4J, Predictive Insights, and Splunk.
Experience with Deep Learning Frameworks.
Experience with interpretability of deep learning models.
Python experience with ML libraries, such as SciKit Learn, TensorFlow, and Keras on both CPU and GPU compute architectures.