Data Scientist

Leidos•Bethesda, MD

11d•Onsite

About The Position

Leidos is seeking a Data Scientist to join their team. This role involves performing research-level data analytics and supporting programs that advance the state of the art in research and advanced machine learning, natural language processing, and data fusion applications in mission-focused big data analytics. The Data Scientist will be part of a research-focused team working to advance national security objectives, produce and analyze results, disseminate findings, and contribute to publications and presentations with actionable intelligence insights. The position is located at the customer site in Bethesda, MD.

Requirements

B.S. Degree in a quantitative or analytical field such as Computer Science, Mathematics, Economics, Statistics, Engineering, Physics, or Computational Social Science with 2+ years of experience; or Master’s degree or equivalent graduate degree including certificate-based advanced training courses with less than 2 years of experience.
Ability to obtain a TS/SCI with Polygraph post hire.
Experience in data science, analytics or quantitative intelligence analysis, and demonstrating progressive technical development and outcomes.
Proficiency in one or more scripting languages such as Python.
Deployment of data science applications (e.g. Streamlit) using Docker, Kubernetes, and/or OpenShift.
Experience with information retrieval and search, e.g. Elastic Stack (Elasticsearch and Kibana) and/or Structured Query Language (SQL).
Experience working with a hybrid team of analyst, engineers, and developers to conduct research, and build and deploy complex, but easy-to-use algorithms and analytical platforms.
Previous experience performing Data Science or Research in data analytics or big data, i.e. data that won’t fit in memory.
Track record of active learning and creative problem solving.
Ability to analyze and assess software development or data acquisition requirements and determine optimum, cost-effective solutions.
Familiarity using git or other version control technologies.

Nice To Haves

A significant share of your data analytics experience in direct support of military or intelligence community customers, demonstrating progressive technical development and mission-focused outcomes.
Significant experience dealing with at least two of the following data classes: forensic media (i.e. DOMEX); open source, publicly available information (PAI); measurement and signatures intelligence (MASINT); or cybersecurity and cyber forensics.
Experience with Knowledge Graphs and KG tech such as neo4j or graph ML.
Experience developing predictive algorithms, image classifiers, object detectors, and others.
Familiarity with social network analysis, supply chain analysis, forensic accounting, pattern of life, natural language processing, social media analysis, classification algorithms, and/or image processing.
Experience blending analytical methodologies and leveraging existing COTS/GOTS/OS tools in an unconventional manner.
Experience with an on-prem, air gapped environment and/or Amazon Web Services (AWS/C2S).
Familiarity with hardware platforms, e.g., CPUs, GPUs, FPGAs, etc.

Responsibilities

Work closely with a tight-knit team of data scientists, as well as a larger team of software developers, network engineers, senior investigators, program managers, researchers, and data analysts to design, build, and optimize a Data Science platform to produce and analyze results, disseminate findings, and contribute to publications and presentations.
Work on small projects analyzing a variety of big data covering national security, cyber security, business intelligence, online social media, human behavior and more.
Support multiple simultaneous projects and take open-ended or high-level guidance, independently and collaboratively make discoveries that are mission-relevant, and package and deliver the findings to a non-technical audience.
Bring intellectual curiosity, quantitative acumen, and customer-focus to identify novel sources of data across a range of fields, to improve the performance of predictive algorithms, and to encourage user adoption of high-end data analytics platforms in partnership with a highly qualified, highly motivated team.
Leverage strong background in research design, exploratory analysis, quantitative methods, user interface application design, and experience with customer outreach and engagement.