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As a Data Scientist, you will leverage data exploration, analysis, and machine learning to provide insights and solutions for clients, using various data sources and tools to address complex challenges.

Develop predictive models, algorithms, quantitative analyses, and visualizations from structured and unstructured data. Extract insights from databases and APIs, apply machine learning and NLP techniques, lead complex solution development, and advise clients on data-driven decisions. The role requires TS/SCI clearance with polygraph and involves Python, SQL, AI engineering, production ML pipelines, and distributed computing frameworks.

Analyze structured and unstructured datasets using Python, R, and SQL; perform data cleansing, statistics, visualization, and machine learning; develop dashboards and lightweight applications; integrate data systems; guide algorithm development; and advise clients on data-driven decisions, data strategy, governance, and infrastructure.

Develop algorithms, predictive models, and analytical systems from structured and unstructured data. Perform data exploration, cleaning, mining, visualization, modeling, and dashboard development using Python, SQL, or R. Apply machine learning, AI, NLP, and statistical techniques to answer client questions and support informed decisions across public and private-sector challenges. Collaborate with clients and work in classified environments requiring Secret clearance.

Develop and enhance C++ software, analyze requirements, resolve software issues, and support solution architecture across projects. Work under direct supervision to solve routine problems and escalate complex issues. Apply C++ fundamentals, debugging, testing, and collaborative problem-solving skills. Preferred experience includes Agile development, modeling and simulation frameworks such as AFSIM, large codebases, and CI/CD tools including Git, Jira, and Bamboo. A Secret clearance or eligibility to obtain one is required.

Analyzes structured and unstructured data to identify insights and solve client problems. Responsibilities include data exploration, cleaning, analysis, visualization, predictive modeling, quantitative analysis, algorithm development, and applying machine learning, artificial intelligence, or natural language processing. The role collaborates with clients and uses Python and other data technologies to produce objective, actionable answers for public- and private-sector challenges.

Build, operate, secure, and modernize cloud infrastructure across AWS, GovCloud, and Azure. Develop infrastructure as code and CI/CD pipelines, administer F5 BIG-IP and Splunk, automate infrastructure operations, and deploy containerized workloads using Kubernetes, EKS, Helm, and Argo CD. Collaborate with architects and stakeholders to deliver managed cloud platforms, support mission requirements, and validate AI-generated infrastructure code. Candidates must be able to obtain a Secret clearance and hold a qualifying DoD 8140 IAT Level II certification.

Provide strategic and tactical advice and develop cloud-based learning solutions (LMS) to support training initiatives. Lead technical implementations, conduct needs assessments, gather and document technical requirements, build client relationships in government/professional services, work on Agile teams, mentor or supervise staff, and support security-clearance processes.

Conduct security control assessments across complex technical environments using NIST SP 800-53 and the Risk Management Framework. Review documentation, interview stakeholders, perform technical testing, identify deficiencies, assess residual risk, and recommend remediation. Evaluate network, system, application, cloud, and cybersecurity controls while producing assessment reports supporting authorization decisions. Monitor POA&M items, assess vulnerabilities, identify advanced threats, and communicate security risks to technical and senior-management audiences.

Leads enterprise security operations modernization for government, critical infrastructure, and regulated-industry clients. Designs AI-enabled security architectures using automation, orchestration, threat intelligence, cloud security, zero trust, and cyber resilience. Conducts risk assessments, develops transformation roadmaps, advises executive stakeholders, evaluates security platforms and OEM capabilities, and leads multidisciplinary technical teams. The role also addresses Agentic AI governance, autonomous security operations, cyber risk quantification, compliance, and enterprise security investment decisions.