Data Scientist, Level 3 at Independent Software

Annapolis Junction, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

14 Apr, 26

Salary

0.0

Posted On

14 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, Statistical Modeling, Data Normalization, Data Visualization, Workflow Automation, Exploratory Data Analysis, Hypothesis Testing, CNE Concepts, AI/ML Frameworks, Problem-Solving, Data Processing, Modeling and Prediction, Analytical Tools, Communication Skills

Industry

Software Development

Description

What You Will Do: As a Data Scientist Level 3 at Independent Software, you will play a mission-critical role in applying advanced data science, artificial intelligence, and machine learning techniques to complex national security challenges. In this role, you will support cyber operations by assessing large language models (LLMs) and advanced analytics to determine their effectiveness and applicability for Computer Network Exploitation (CNE) capability integration and operational utilization. You will work closely with the CNO community, supporting cyber mission tools and capabilities where familiarity with CNE concepts, workflows, and tooling is strongly preferred. Your work will focus on transforming complex, large-scale, and often unstructured data into actionable intelligence through statistical modeling, machine learning, and data-driven discovery. Leveraging strong Python skills, workflow automation, data normalization, and visualization techniques—particularly within Jupyter Notebooks—you will develop analytical tools, assess model performance, and communicate results to both technical and non-technical stakeholders. This role is ideal for a mathematically and statistically grounded professional who is inquisitive, discovery-oriented, and motivated to apply AI/ML in direct support of mission outcomes. Key Responsibilities: Apply data science expertise across at least two of the following domains: Foundations: Mathematical, statistical, and computational theory and application Data Processing: Data curation, normalization, transformation, visualization, reproducibility, and pipeline automation Modeling and Prediction: Statistical modeling, inference, forecasting, machine learning, and domain-specific analytics Assess large language models (LLMs) to determine effectiveness and applicability for CNE capability integration and operational use. Support the CNO community by analyzing data related to cyber tools, techniques, and capabilities. Perform data normalization, statistical analysis, and visualization to support operational decision-making. Draw conclusions from large, complex datasets using a combination of mathematical, statistical, and domain knowledge. Develop and apply analytic models and quantitative techniques tailored to unstructured or incomplete datasets with national security constraints. Translate mission and analytical requirements into technical data specifications and analytical workflows. Guide others in interpreting analytical results and model outputs. Effectively communicate complex technical concepts to diverse audiences, including non-technical stakeholders. Required Skills and Qualifications: Proficiency in Python, including experience developing analytics in Jupyter Notebooks. Strong background in mathematics and statistics, with applied experience in machine learning and statistical modeling. Hands-on experience working with large-scale, complex, and unstructured datasets. Experience with data normalization, transformation, and visualization techniques. Familiarity with AI/ML frameworks and assessing model performance and applicability. Experience supporting or analyzing cyber operations, with familiarity in Computer Network Exploitation (CNE) concepts strongly preferred. Experience with exploratory data analysis, hypothesis testing, and inference modeling. Workflow automation experience, including optimization of data pipelines and ensuring reproducible analytics. Strong problem-solving skills with an inquisitive, discovery-focused mindset. Education and Experience: Minimum Qualifications (One of the following): Master’s degree with 8 plus years of relevant experience Bachelor’s degree with 10 plus years of relevant experience Associate degree with 12 plus years of relevant experience Acceptable Degree Fields: Mathematics, Applied Mathematics, Statistics, Machine Learning, Data Science, Operations Research, or Computer Science Related fields such as Computer Information Systems, Engineering, or Physical Sciences with a strong computational focus Other scientific disciplines may qualify if accompanied by 5 or more upper level courses in mathematics 300 level or higher and or computer science Broader degrees may be accepted if supported by a Data Science Certificate from an accredited institution Clearance Requirement: Must possess an active TS SCI with appropriate Polygraph to be considered for this role Why Choose Independent Software: At Independent Software, our people are the mission. We’ve built a company around collaboration, integrity, and innovation and we make sure our team has the tools and support to grow, succeed, and thrive. When you join us, you will: Support critical national security missions that matter Be part of a close-knit, employee-first culture where your voice is heard Expand your skills through ongoing training, mentorship, and career development Enjoy competitive compensation, generous benefits, and work-life balance Ready to take the next step in your career? Join us and be part of something bigger. Apply today. We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Responsibilities

The Data Scientist Level 3 will apply advanced data science techniques to national security challenges, focusing on transforming complex data into actionable intelligence. Responsibilities include assessing large language models and supporting the CNO community with data analysis related to cyber operations.