Senior Data Scientist

Confirmed live in the last 24 hours

Clarity Innovations

Bluegrass Station, Lexington, Kentucky

On-site

Posted April 6, 2026

Job Description

Clarity Innovations is a trusted national security partner, dedicated to safeguarding our nation’s interests and delivering innovative solutions that empower the Intelligence Community (IC) and Department of Defense (DoD) to transform data into actionable intelligence, ensuring mission success in an evolving world.

Our mission-first software and data engineering platform modernizes data operations, utilizing advanced workflows, CI/CD, and secure DevSecOps practices. We focus on challenges in Information Warfare, Cyber Operations, Operational Security, and Data Structuring, enabling end-to-end solutions that drive operational impact.

We are committed to delivering cutting-edge tools and capabilities that address the most complex national security challenges, empowering our partners to stay ahead of emerging threats and ensuring the success of their critical missions. At Clarity, we are people-focused and set on being a destination employer for top talent, offering an environment where innovation thrives, careers grow, and individuals are valued. Join us as we continue to lead innovation and tackle the most pressing challenges in national security.

Role
This role is for a Senior Data Scientist on a close-knit team supporting Special Operations Forces Support Activity (SOFSA), a U.S. Special Operations Command program at Bluegrass Station in Lexington Kentucky. SOFSA provides flexible and highly responsive logistics support services to ensure that the equipment readiness requirements of the special operations war fighter are met. As a subject matter expert, the Senior Data Scientist will leverage their experience to gather and derive insights from complex data, assist the command with development initiatives, and facilitate digital transformation efforts. The work done in this role has a direct impact on mission readiness as the team's efforts go toward making a more resilient and data-driven organization.

Responsibilities

A Senior data scientist will have skills sets of both data analysts and data engineers. Senior Data scientists are responsible for designing, implementing, and maintaining a data pipeline. In addition, Senior Data Scientists shall interpret and analyze complex sets of data, as well as plan, execute, and manage ML projects with cloud-native platforms and advanced ML solutions. They understand some of the most challenging processes, technologies, and can leverage a vast array of methodologies in the field, such as data mining, natural language programming, and machine learning. Senior Data scientists must have a combination of skills that includes programming, mathematical modeling, statistics, and domain knowledge. They must combine an advanced math and statistics background with programming, domain knowledge, and communication skills to analyze data, create applied mathematical models, and present results in a form useful to the organization. They must also be able to understand and manipulate structured and unstructured large data sets, which requires proficiency in distributed SQL programming, relational and non-relational data queries, general programming languages (such as Python and R,) and machine learning techniques.

The Senior Data Scientist shall perform the following tasks:
• Interpret and analyze data using exploratory mathematic and statistical techniques based on the scientific method.
• Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data.
• Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.
• Coordinate with Data Engineers to build Data environments providing data identified by other data professionals.
• Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities.
• Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques.
• Design

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