IT Internal Auditor - Advisor
Fannie Mae•Reston, VA
•$141,000 - $184,000•Hybrid
About The Position
Our team of trusted audit professionals evaluates every aspect of Fannie Mae’s IT environment. From on-premises environments to cutting edge cloud services, our audits cover the broad range of exciting technologies Fannie Mae uses, providing a challenging environment with tremendous opportunities for personal growth. Within IT Audit, the infrastructure team focuses on evaluating Fannie Mae’s complex environment of IT processes, systems, and services. We conduct audits focused on highly visible topics, such as cyber security, IT Governance, resiliency, and the management of the various operating systems and platforms used by Fannie Mae. In this position, you will push us forward in our journey to increase the use of advanced data analytics, modeling, and AI to more effectively assess the IT environment.
Requirements
- Minimum Required Experience 6+ years of experience in programming in data analytics related languages, such as Python, R, or JavaScript.
- 3+ years in ML engineering, including 3+ years hands-on with Generative AI/LLMs and 2+ years with knowledge graph technologies.
- Curiosity and adaptability learning and responsibly applying new techniques, including artificial intelligence, to reimagine how we work.
- Bachelor's Level Degree (Required)
Nice To Haves
- Master’s degree in Computer Science, Statistics, Mathematics, or related area of study
- Ability to apply statistical or computational methods to real-world data and tailoring analysis to answer complex questions or problems
- Strong coding skills and experience with data analytics related languages, such as Python (including SciPy, NumPy, and/or PySpark) and/or Scala.
- Visualization: Strong skills in identifying, designing, and implementing visualizations of various data sets
- Experience with visualization tools (e.g., PowerBi, Tableau, Plotly, Seaborn)
- Generative AI: Proven experience building AI solutions using advanced prompt engineering (Chain of Thought, Tree of Thought) and designing and deploying RAG pipelines
- Experience with validation of LLM outputs and reduction of hallucinations
- Knowledge of Agentic AI architecture, and knowledge graph integration with LLMs (e.g., GraphRAG, ontology-driven prompt engineering, hybrid reasoning systems).
- Hands-on work with vector databases (Pinecone, Chromadb) and frameworks like LangChain/LlamaIndex for orchestration.
- Experience with fronter LLMs
- Classical Machine Learning: Strong foundation and experience in supervised/unsupervised learning (regression, classification, clustering, ensemble methods).
- Experience combining classical ML (e.g., feature engineering, dimensionality reduction) with GenAI systems for improved robustness/accuracy.
- Proficient in Natural language processing (NLP) and Natural language generation (NLG)
- Tools: Proficient in Python, PyTorch/TensorFlow, and ML libraries (Scikit-learn, Hugging Face Transformers).
- Production experience with AWS/GCP (SageMaker, S3, Lambda)
- Demonstrated experience building data pipeline to process structured and unstructured data sources, data cleansing/prep for analysis
- Excellent written and verbal communication skills
- Critical thinking and data analytic skills
Responsibilities
- Identify, review, and acquire data from primary or secondary data sources.
- Establish associated data interfaces and ingestion processing frameworks.
- Implement new statistical modeling capabilities that help identify risks and control gaps in the IT environment.
- Apply and build new advanced analytic capabilities to support the integration of data and statistical models or algorithms into day-to-day IT audit work.
- Apply industry practices in research and testing to product development, deployment, and maintenance.
- Create new modeling/statistical applications to support risk measurement and automated control testing.
- Design and implement data visualizations, technical documentation, and non-technical presentation materials to communicate complex ideas and findings to audit teams and clients.
- Develop Retrieval-Augmented Generation (RAG) and Agentic AI workflows.
- Integrate LLMs (Gemini, Claude, GPT-4o) into the audit process, both for audit data and audit evidence.
- Act as a source of knowledge related to AI and data analytics.
- Build and maintain relationships with business partners.
Benefits
- Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well-being.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
