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Ai Risk Analyst Jobs in Frederick, MD (NOW HIRING)

You will lead "Gap Analysis" and "Risk Management" exercises to ensure all AI deployments are trustworthy and transparent. • Oversight of Complex Modeling & High-Dimensional Data Pipelines • ...

... Gap Analysis' and 'Risk Management' exercises to ensure all AI deployments are trustworthy and transparent. • Direct the design and implementation of high-throughput data pipelines capable of ...

You will lead "Gap Analysis" and "Risk Management" exercises to ensure all AI deployments are trustworthy and transparent. 2. Oversight of Complex Modeling & High-Dimensional Data Pipelines

You will lead "Gap Analysis" and "Risk Management" exercises to ensure all AI deployments are trustworthy and transparent. 2. Oversight of Complex Modeling & High-Dimensional Data Pipelines

Associate Director of AI and Data

Rockville, MD · On-site

$60K - $60K/yr

... analyzing petabyte-scale datasets. • Oversee the development of predictive models for ... Risk Mitigation" volumes. • Galvanize relationships with key federal stakeholders (Project ...

Assessment Analyst

Leesburg, VA · On-site +1

$87K - $95K/yr

AI, we have expanded our capabilities to include advanced cyber risk quantification and analytics, enabling organizations to better understand, measure, and communicate risk. Together, we deliver ...

Assessment Analyst

Leesburg, VA · On-site

$88 - $95/hr

AI, we have expanded our capabilities to include advanced cyber risk quantification and analytics, enabling organizations to better understand, measure, and communicate risk. Together, we deliver ...

AI Engineer

Rockville, MD · Remote

$140K/yr

AI Engineer Location: Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible ... Databricks, Snowflake, Spark/PySpark * Healthcare analytics, fraud/waste/abuse detection, risk ...

AI Engineer

Rockville, MD · On-site

$140K/yr

AI Engineer Location: Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible ... Databricks, Snowflake, Spark/PySpark * Healthcare analytics, fraud/waste/abuse detection, risk ...

AI Engineer Location: Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible ... Databricks, Snowflake, Spark/PySpark * Healthcare analytics, fraud/waste/abuse detection, risk ...

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

The engineer will set technical strategy, establish evaluation and risk controls, and mentor a team ... Experience analyzing structured and unstructured documents, including charts and disclosures ...

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Ai Risk Analyst information

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How much do ai risk analyst jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for ai risk analyst in Frederick, MD is $40.25, according to ZipRecruiter salary data. Most workers in this role earn between $29.62 and $48.99 per hour, depending on experience, location, and employer.

What is an AI risk analyst?

AI Risk Analysts are professionals who assess, monitor, and manage the risks associated with the development and deployment of artificial intelligence systems. Their work involves identifying potential threats such as bias, security vulnerabilities, ethical concerns, and compliance issues that could arise from using AI technologies. They collaborate with data scientists, engineers, and compliance teams to develop risk mitigation strategies and ensure that AI systems operate safely, ethically, and in accordance with relevant regulations.

What skills and qualifications are needed to be an AI risk analyst?

To thrive as an AI Risk Analyst, you need a strong foundation in data analysis, risk assessment, and an understanding of AI/ML technologies, typically supported by a degree in computer science, statistics, or a related field. Familiarity with risk management frameworks, AI auditing tools, and certifications such as CRISC or AI ethics credentials is often required. Excellent problem-solving, critical thinking, and communication skills help in identifying risks and conveying complex findings to stakeholders. These skills are crucial to ensure responsible AI deployment, mitigate potential risks, and maintain regulatory compliance.

How does an AI risk analyst collaborate with cross-functional teams to assess and mitigate risks?

AI Risk Analysts work closely with data scientists, engineers, compliance officers, and business leaders to identify, evaluate, and mitigate risks associated with AI systems. They facilitate risk assessment workshops, gather input from technical and non-technical stakeholders, and ensure that risk controls are integrated into AI development processes. Effective communication and documentation are crucial, as analysts must translate complex technical risks into actionable recommendations for diverse teams. This collaborative approach helps ensure that AI solutions are both innovative and aligned with regulatory and ethical standards.

What is the difference between Ai Risk Analyst vs Data Scientist?

AspectAi Risk AnalystData Scientist
Required CredentialsBachelor's in Risk Management, Data Science, or related fields; certifications in AI or risk analysisBachelor's or Master's in Data Science, Statistics, or Computer Science; certifications in data analysis or machine learning
Work EnvironmentFinancial institutions, insurance companies, or tech firms focusing on risk assessmentTech companies, research labs, or any industry leveraging data for insights
Employer & Industry UsagePrimarily in finance, insurance, and risk-focused sectorsAcross various industries including tech, healthcare, finance, and marketing

The main difference is that an Ai Risk Analyst specializes in assessing and managing risks related to AI systems, often within financial or risk-focused industries. In contrast, a Data Scientist analyzes large datasets to extract insights across diverse sectors. While both roles require strong analytical skills and knowledge of AI and data tools, the Ai Risk Analyst focuses more on risk mitigation specific to AI applications.

How much do AI risk analysts make?

AI risk analysts typically earn between $70,000 and $130,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in AI safety and risk management can earn higher salaries, often exceeding $150,000. The role often requires knowledge of AI systems, risk assessment, and relevant certifications.

How to become an AI risk analyst?

To become an AI risk analyst, candidates typically need a strong background in computer science, data analysis, or related fields, along with knowledge of AI systems and risk management principles. Relevant skills include programming, statistical analysis, and understanding of AI safety and ethics, often supported by certifications or advanced degrees. Experience with AI tools and risk assessment frameworks is also valuable.

What does an AI risk analyst do?

An AI risk analyst evaluates potential risks associated with artificial intelligence systems, including safety, ethical concerns, and unintended consequences. They analyze data, develop risk mitigation strategies, and often use tools like risk assessment frameworks to ensure AI deployment aligns with safety standards and regulations.

Will AI take over AI Risk Analyst jobs?

AI Risk Analysts evaluate and manage risks associated with artificial intelligence systems, a role that requires specialized knowledge of AI technologies, ethics, and safety protocols. While AI tools can assist in data analysis and risk assessment, human expertise remains essential for interpreting complex issues and making strategic decisions, so the job is unlikely to be fully automated in the near term.

What are popular job titles related to Ai Risk Analyst jobs in Frederick, MD?

For Ai Risk Analyst jobs in Frederick, MD, the most frequently searched job titles are:

What job categories do people searching Ai Risk Analyst jobs in Frederick, MD look for?

The top searched job categories for Ai Risk Analyst jobs in Frederick, MD are:

What cities near Frederick, MD are hiring for Ai Risk Analyst jobs?

Cities near Frederick, MD with the most Ai Risk Analyst job openings:

Assistant Director of AI and Data

Axle

Rockville, MD • On-site

Full-time

Re-posted 22 days ago


Job description

Job Summary:
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations. They are seeking a visionary Assistant Director of AI and Data to lead the development and deployment of AI-driven solutions for federal health agencies, bridging advanced computational science and clinical research.
Responsibilities:
• Strategic Leadership of the AI/ML Roadmap
• Visionary Architecture: Architect and execute a comprehensive AI/ML strategy that aligns Axle’s technical capabilities with the NIH Strategic Plan for Data Science (2025–2030). You will define the long-term vision for integrating Generative AI, Large Language Models (LLMs), and Agentic Workflows into federal research environments, moving beyond static analysis to active, AI-assisted discovery.
• Platform Evolution (Polus): Spearhead the evolution of the Polus platform, transitioning it from a robust image analysis tool into a fully integrated, multi-modal research ecosystem. You will oversee the roadmap for new feature development, ensuring scalability, security, and interoperability across cloud environments (AWS/GCP/Azure) using containerized architectures (Docker/Kubernetes).
• AI Governance & Compliance: Establish and enforce rigorous AI Governance frameworks. You will operationalize the NIST AI Risk Management Framework (RMF) across all projects to ensure fairness, interpretability, and compliance with federal ethical standards. You will lead "Gap Analysis" and "Risk Management" exercises to ensure all AI deployments are trustworthy and transparent.
• Oversight of Complex Modeling & High-Dimensional Data Pipelines
• Petabyte-Scale Engineering: Direct the design and implementation of high-throughput data pipelines capable of ingesting and analyzing petabyte-scale datasets (genomics, proteomics, EHR). You will ensure these systems adhere to FAIR data principles (Findable, Accessible, Interoperable, Reusable), facilitating seamless data sharing across NIH institutes and global research centers.
• Translational Science De-risking: Oversee the development of predictive models for translational science, focusing on "de-risking" drug discovery and clinical trial design. This involves guiding technical teams in the application of deep learning techniques to identify molecular targets, predict therapeutic outcomes, and simulate clinical scenarios (Digital Twins).
• Operational Excellence (MLOps): Optimize MLOps and DevSecOps processes to ensure the rapid, secure deployment of models from prototype to production. You will champion a culture of "automation first," reducing time-to-insight for researchers by streamlining the transition from Jupyter notebooks to containerized, cloud-native services.
• Business Development & Federal Growth (Capture Support)
• Lead Solution Architect: Partner with the Growth and Capture teams to drive new business acquisition. You will serve as the Lead Solution Architect for major proposal efforts ($50M+), authoring technical volumes, developing win themes, and creating compelling solution graphics that demonstrate Axle’s technical differentiation.
• Proposal Authorship: Personally write key sections of technical proposals, including the "Technical Approach," "Staffing Plan," and "Risk Mitigation" volumes. You will translate complex agency requirements into winning narratives that score highly with federal evaluators.
• Client Liaison: Galvanize relationships with key federal stakeholders (Project Officers, CIOs, Lab Chiefs). You will act as the primary technical liaison, translating complex agency requirements into deliverable technical solutions and presenting these visions in competitive "Black Hat" sessions and oral presentations.
• Mentorship of Data Scientists & Engineers
• Interdisciplinary Team Building: Cultivate a high-performance, interdisciplinary team culture. You will manage and mentor a diverse group of data scientists, bioinformaticians, and software engineers, fostering an environment of psychological safety where "expert" scientific knowledge seamlessly integrates with "agile" engineering practices.
• Continuous Learning: Drive continuous learning and upskilling initiatives. You will establish internal "Communities of Practice" for AI and Data Science, ensuring that Axle’s workforce remains at the bleeding edge of technologies like Graph Neural Networks and Federated Learning.
• Democratization of AI: Democratize access to AI tools within the client environment. You will lead efforts to create "low-code/no-code" interfaces and training programs that empower non-technical NIH researchers to utilize advanced analytics independently.
Qualifications:
Required:
• Ph.D. in Computer Science, Bioinformatics, Computational Biology, Data Science, or a related quantitative discipline is highly preferred to ensure peer-level credibility with NIH scientists.
• Alternatively, a Master’s degree in one of the above fields with exceptional, demonstrated leadership experience in a federal or research-intensive setting will be considered.
• 8–10+ years of progressive experience in data science, AI/ML engineering, or computational biology, with a focus on high-dimensional data.
• 3–5+ years of leadership experience managing cross-functional teams (e.g., managing both PhD researchers and software developers) in a matrixed organization.
• Demonstrated experience with Federal Business Development, including writing technical proposals and supporting capture activities for contracts valued at $15M+.
• Proven track record of delivering complex AI/ML solutions in a regulated environment, with specific familiarity with HIPAA, FedRAMP, or NIST AI RMF compliance.
• Expert-level understanding of Deep Learning frameworks (PyTorch, TensorFlow), Classical Machine Learning (Scikit-Learn), and Generative AI architectures (Transformers, LLMs, RAG).
• Proficiency in Python (primary) and R (secondary); familiarity with Java or C++ (for Polus backend optimization) is a strong plus.
• Extensive experience with Cloud-Native AI pipelines on AWS (SageMaker, HealthLake), GCP (Vertex AI, BigQuery), or Azure. Knowledge of the NIH STRIDES initiative and cloud economics is essential.
• Mastery of big data technologies (Spark, Databricks) and workflow orchestration tools (Airflow, Nextflow, Cromwell).
• Strong knowledge of containerization (Docker, Kubernetes), CI/CD pipelines (GitHub Actions, Jenkins), and model monitoring/governance tools.
• Experience with advanced visualization tools (DeepZoom, WebGL) and platform development (building APIs, microservices).
Preferred:
• Direct experience working with NIH, NCATS, NIAID, or similar federal health agencies. Understanding of the specific data challenges within the federal health sector is highly valued.
• Contributions to or leadership of open-source scientific software projects. Specific familiarity with the Polus platform or the National COVID Cohort Collaborative (N3C) data enclave is a distinct advantage.
• Demonstrated experience implementing the NIST AI Risk Management Framework (Map, Measure, Manage, Govern) in a real-world setting.
• Specialized knowledge in High-Content Imaging, Cheminformatics, Genomics, or Real-World Data (RWD) analytics.
Company:
At Axle, we are driven by the mission to accelerate discovery and enhance organizational outcomes by revolutionizing operations with our innovative solutions. Founded in 2002, the company is headquartered in Rockville, USA, with a team of 501-1000 employees. The company is currently Late Stage.