Nebraska Staffing
Join Leidos as a Data Scientist and Help Drive Cutting-Edge Analytics
Leidos is seeking a forward-thinking Data Scientist with a strong foundation in statistical analysis, data ingestion and processing, and deep expertise in methods and analytics development. This role supports a high-impact data analytics program for our customer, where innovation meets mission-critical insights. You'll be part of a collaborative team, developing sophisticated analytics through automated solutions, managing code repositories, and crafting documentation that empowers the broader enterprise. Primary Responsibilities: Partner with the experimentation team to design and automate analytics and analytic methods using Python, R, or similar tools Identify and ETL relevant datasets to fuel powerful insights Build and train multilevel regression models to uncover complex patterns Create and deploy compelling visualizations that bring analytic results to life Leverage GitHub to store, version, and document analytic processes and code Contribute to customer-facing analytic products with precision and clarity Manage the hardware, network, security, and software infrastructure essential for analytical success Basic Qualifications: Must hold a current TS/SCI with Polygraph clearance on day 1. Master's Degree in Statistics, Mathematics, Data Analytics, or a related field with 15 years of relevant experience, or a Bachelor's Degree with 20 years of relevant experience. Proven experience with at least one programming language such as Python or R Hands-on experience with data science libraries like Pandas, NumPy, and SciPy Skilled in relational databases, SQL, and API-based data querying Preferred Qualifications: Experience contributing to GitHub repositories and using Git for version control Exceptional coordination and collaboration skills Come break things (in a good way). Then build them smarter. We're the tech company everyone calls when things get weird. We don't wear capes (they're a safety hazard), but we do solve high-stakes problems with code, caffeine, and a healthy disregard for "how it's always been done."
Leidos is seeking a forward-thinking Data Scientist with a strong foundation in statistical analysis, data ingestion and processing, and deep expertise in methods and analytics development. This role supports a high-impact data analytics program for our customer, where innovation meets mission-critical insights. You'll be part of a collaborative team, developing sophisticated analytics through automated solutions, managing code repositories, and crafting documentation that empowers the broader enterprise. Primary Responsibilities: Partner with the experimentation team to design and automate analytics and analytic methods using Python, R, or similar tools Identify and ETL relevant datasets to fuel powerful insights Build and train multilevel regression models to uncover complex patterns Create and deploy compelling visualizations that bring analytic results to life Leverage GitHub to store, version, and document analytic processes and code Contribute to customer-facing analytic products with precision and clarity Manage the hardware, network, security, and software infrastructure essential for analytical success Basic Qualifications: Must hold a current TS/SCI with Polygraph clearance on day 1. Master's Degree in Statistics, Mathematics, Data Analytics, or a related field with 15 years of relevant experience, or a Bachelor's Degree with 20 years of relevant experience. Proven experience with at least one programming language such as Python or R Hands-on experience with data science libraries like Pandas, NumPy, and SciPy Skilled in relational databases, SQL, and API-based data querying Preferred Qualifications: Experience contributing to GitHub repositories and using Git for version control Exceptional coordination and collaboration skills Come break things (in a good way). Then build them smarter. We're the tech company everyone calls when things get weird. We don't wear capes (they're a safety hazard), but we do solve high-stakes problems with code, caffeine, and a healthy disregard for "how it's always been done."