Data Scientist III (R-00138)
True Zero Technologies, a veteran-owned small business, was founded on the principle that the purposeful enablement of people and technology in an organization directly ties to the quality of its outcomes. True Zero recognizes that those outcomes begin and end with our people, and that is what we have built a community of like-minded, driven, and passionate individuals and innovators who are aligned in a common goal of delivering top-tier services to our customers. Our culture and commitment have been recognized through numerous accolades, including being named one of the Best Places to Work in 2023 in two categories (“Prosperous and Thriving” ($5MM-$50MM in gross revenue) and “Mid-Atlantic Region” (DC, DE, MD, NC, VA, WV)), and again in 2025 as a Best Places to Work honoree. In addition, True Zero earned coveted spots on the Inc. 5000 list of fastest-growing companies in America in 2022, 2023, and 2025, a testament to our sustained growth driven by our people-first approach and unwavering dedication to excellence.
This role will be responsible for design and deliver data science and machine learning solutions that improve security and operational decision-making. Builds pipelines and models, validates performance, and deploys analytics in a maintainable way. Leads technical solution design and guides a team through implementation. Enables higher-value automation and insight generation from enterprise telemetry and datasets.
Job Responsibilities
- Design and implement ML/data science solutions aligned to mission/security needs.
- Build data pipelines, feature engineering approaches, and model evaluation methods.
- Create operational analytics, visualizations, and decision-support outputs.
- Lead technical design and execution of data science workstreams.
- Support containerized deployment and scalable engineering patterns where required.
Job Qualifications
- Master’s or PhD in a quantitative field such as: Statistics, Engineering, Computer Science or Economics required.
- 5+ years in ML engineering / data science / data engineering.
- Experience designing a technical solution and leading a team through implementation.
- Experience with OOP languages (as listed).
- Experience with Kubernetes and Docker.
- A certified analytics credential as specified in the labor category table.
- Must have at least a CertifiedAnalytics Professional (CAP) certification.
- Must be eligible for Secret clearance.