Data Scientist
At a glance
Mid-level Data Science role at Leidos. Springfield · full-time · $92,300–$166,850 base.
dataroles summary, based on the employer's posting.
What you'll do
- Gather and analyze data, then clean, structure and maintain it in database management systems
- Run one-off analyses and explain findings clearly, using visuals and narrative to make quantitative results actionable
- Build and support cloud applications and extraction tools for moving data and production workflows
- Write Python scripts in ArcGIS to make production work more efficient
- Convert or migrate data and help redesign business processes
What you bring
- A quantitative bachelor’s degree with ten years of relevant experience, or a quantitative master’s with seven years
- Experience with programming, spatial analysis, data mining, database structures, visualization and statistical or mathematical modeling
- A record of handling data science projects, spatio-temporal analysis and large-scale data processing with Databricks, Apache Spark or similar
- Active TS/SCI clearance and eligibility for polygraph approval
Who this fits
This mid-level role suits someone with substantial quantitative and data science experience who can work across analysis, data migration and production tooling. The position supports a customer in Springfield, Virginia and requires an active TS/SCI clearance with the ability to obtain polygraph approval.
From the employer
Leidos has an opening for a Exploitation Specialist/Data Scientist- Senior supporting our customer in Springfield Virginia.
Primary Responsibilities
Collect process data and perform data analysis.
Integrate centralized protect and maintain data in DBMS.
Clean, condition, and organize data.
Perform ad hoc analysis and present results in a clear manner.
Communicate complex quantitative analysis in a clear, precise and actionable manner using storytelling/visualization.
Create/deploy/maintain cloud applications to support migration of data and production processes
Create/deploy/maintain tools to extract features data and metadata from a variety of sources, including raster to vector, vector to vector text, text to vector and text database.
Write/maintain Python scripts in ArcGIS to improve efficiency of the production process.
Support business processing re-engineering.
Perform data conversion/migration.
Basic Qualifications
Typically requires a Bachelor’s degree and 8 – 12 years of prior relevant experience or Master’s degree with 6 – 10 years of prior relevant experience.
Quantitative BS + 10 yrs or quantitative MS + 7 yrs.
Programming (Python/Pig/Java/JS/SQL/R), spatial analysis, data mining, database structures, visualization.
Statistical/mathematical modeling.
Experience managing data science projects, data mining, spatio-temporal analysis. Docker/Jupyter Hub/GIT.
Experience with “big data” processing and analytics (Databricks/Apache Spark or similar).
Active TS/SCI with ability to be approved for a Poly
Preferred Qualifications
Quantitative PhD.
Deep learning for data science.
2+ programming languages, 2+ data visualization tools, 2+ cloud technologies.
Windows/Linux command line interface (CLI) experience.
Demonstrated IC experience.
#GEOINTMISSION
#NSBA
If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.
Original Posting:
May 20, 2026For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $92,300.00 - $166,850.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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