Lead Associate — Generative AI & Applied Data Science

Playing an essential role in the U.S. economy Fannie Mae is foundational to housing finance. Here your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home.

Job Description

Were hiring a Lead Associate to join our Applied Data Science team to build and productize advanced AI/ML and generative AI solutions that drive business outcomes. The role partners closely with cross-functional stakeholders (business risk controls and engineering) to deliver production-grade models scalable data products and explainable AI that operate in a regulated financial environment.

We are especially interested in candidates who have experience at a large financial institution are familiar with financial datasets and workflows and have hands-on experience building GenAI / LLM solutions. A PhD in finance economics computer science (or strongly related field) is preferred.

THE IMPACT YOU WILL MAKE

The Lead Associate Generative AI & Applied Data Science role will offer you the flexibility to make each day your own while working alongside people who care so that you can deliver on the following responsibilities:

• Coordinate product and/or business owners across divisions or product lines data engineers and platform teams to define business needs and advise on current capabilities data availability and alternative uses.
• Lead the implementation of new statistical modeling capabilities which requires skillful coordination of multiple processes systems and/or stakeholders.
• Apply advanced analytic capabilities to enhance the delivery of business applications and support the integration of data and statistical models or algorithms.
• Apply new or innovative practices in research and testing to product development deployment and maintenance.
• Design new modeling applications to support risk measurement financial valuation decision making and business performance.
• Design data visualizations technical documentation and non-technical presentation materials to communicate new ideas and high-impact solutions to business partners.

Minimum Required Experiences:

• 4 years of experience.
• Bachelors degreein Computer Science Data Science Engineering Finance Mathematics Physics Statistics Business Analytics or a related field. PhD preferred(see desired).
• Experience working at a large financial institutionand demonstrable familiarity with financial accounting capital or mortgage/loan data and workflows.
• 2 years of relevant industry experiencebuilding large-scale machine learning or deep learning models/systems (for Lead Associate level 3 years is preferred).
• Hands-on programming experience in Python(3 years recommended) and familiarity with Linux-based environments.
• Experience working in cloud environments (e.g. AWS) and comfortable with tools such as SageMaker Jupyter Spark.
• Practical experience with NLP NLG and Large Language Models (LLMs)and GenAI tools (for example: GPT-4 OpenAI APIs LLaMA Claude etc.).
• Demonstrated experience with model development and MLOps workflows (data prep training evaluation CI/CD model deployment monitoring). Familiarity with Git build/deploy tools (Jenkins/GitHub Actions/GitLab CI) and container workflows (Docker/Kubernetes) is expected.
• SQL skills and experience with relational and analytics databases (e.g. Redshift Postgres Oracle Hive EMR).
• Excellent written and verbal skills and the ability to proactively communicate and collaboratewith stakeholders across business engineering and controls teams.

Desired Experiences:

• PhD (preferred)or MS in Finance Economics Computer Science Statistics Math or a related field.
• 3 years building large-scale ML/DL systems in production with at least 1 year of focused deep-learning / LLM/GenAI work.
• Prior experience developing and deploying LLM agents or agentic systems.
• Experience with MLOps platforms (Domino Sagemaker or similar) and CI/CD for ML.
• Deep learning frameworks: TensorFlow Keras PyTorch.
• Applied NLP/GenAI frameworks: Hugging Face transformers LangChain RAG architectures LoRA PEFT LLM fine-tuning approaches.
• Vector search / retrieval: Vector DBs FAISS Milvus Pinecone or cloud equivalents; experience implementing retrieval-augmented generation (RAG).
• NLP toolkits and techniques: spaCy NLTK topic modeling sentiment analysis NER POS tagging TF-IDF text embedding workflows.
• Familiarity with LLM-centric architectures and patterns: agentic programming / LLM Agents Chain-of-Thought Tree-of-Thought Human-in-the-Loop (HITL)design.
• Experience with search and indexing technologies (Elasticsearch / OpenSearch / Solr) and knowledge graphs/ontologies (OWL RDF SPARQL) is a plus.
• Image model knowledge (e.g. ResNet CLIP) is a plus for multimodal use cases.
• Experience building reproducible productionized data workflows and visualizations (Tableau Kibana QuickSight etc.).
• Demonstrated success translating analytics into business impact in a fast-paced cross-functional environment.
• Strong scripting skills (Shell Python) and familiarity with Spark / PySpark for large-scale data processing.
• Comfortable working with ambiguous problems imperfect data and evolving requirements.

Target Pay Range: $141000.00 - $184000.00 a year

Internal Job Title: Enterprise Modeling and Analytics - Data Science - Lead Associate

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Qualifications

Education:

The future is what you make it to be. Discover compelling opportunities at most roles employees are expected to work onsite on a regular basis at their designated office -office work cadence is determined by your manager. Proximity within a reasonable commute to your designated office location is preferred unless the job is noted as open to remote.

Fannie Mae is an equal opportunity employer and considers qualified applicants for employment without regard to race color religion sex national origin disability age sexual orientation gender identity/gender expression marital or parental status or any other protected factor. Fannie Mae is committed to providing reasonable accommodations to qualified individuals with disabilities who are employees or applicants for employment unless to do so would cause undue hardship to the company. If you need assistance using our online system and/or you need a reasonable accommodation related to the hiring/application process please complete this form.

The hiring range for this role is set forth below. Final salaries will generally vary within that range based on factors that include but are not limited to skill set depth of experience certifications and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package Fannie Mae offers a broad range of Health Life Voluntary Lifestyle and other benefits and perks that enhance an employees physical mental emotional and financial well-being. See more here.

Requisition compensation:

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