Senior Data Scientist - AI Developer (Flexible Hybrid)
Company: The Fannie Mae
Location: Washington
Posted on: March 12, 2025
Job Description:
- Full-time
- Target Hiring Range (1): 121000
- Target Hiring Range (2): 158000Company DescriptionAt Fannie
Mae, futures are made. The inspiring work we do helps make a home a
possibility for millions of homeowners and renters. Every day
offers compelling opportunities to use tech to tackle housing's
biggest challenges and impact the future of the industry. You'll be
a part of an expert team thriving in an energizing, flexible
environment. Here, you will grow your career and help create access
to fair, affordable housing finance.Job DescriptionFannie Mae is
expanding its Data Science talent to further push the frontiers of
modeling, AI and advanced analytics. Are you passionate about
advanced analytics algorithms, AI techniques and about creating new
AI solutions and technologies? Do you have creative and innovative
approaches to developing new AI products? We're seeking data
scientists who have domain knowledge or an interest in Generative
AI, large language models, machine learning, natural language
processing, image processing and an interest to apply it to solve
the most complex problems in business.If you are ready for an
exciting opportunity working hands on with the world's most
advanced data science technologies and thrive in a super dynamic
environment where you are being counted on to develop advanced
analytics and AI products, this role is for you:THE IMPACT YOU WILL
MAKEThe Senior Data Scientist - AI Developer 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:
- Collaborate with product and/or business owners, data
engineers, and platform teams to understand business needs and
current capabilities, data availability, and alternative uses.
- Implement new statistical modeling capabilities.
- Apply analytic capabilities and build upon advanced analytic
capabilities to enhance the delivery of business applications, and
support the integration of data and statistical models or
algorithms. Apply industry 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 complex ideas
and solutions to business partners.QualificationsTHE EXPERIENCE YOU
BRING TO THE TEAMMinimum Required Experiences:
- Education: Bachelors degree in Computer Science, Data Science,
Statistics, Physics, Mathematics, or related quantitative
field.
- Experience: 2+ years in ML engineering, including2+ years
hands-on with Generative AI/LLMsand1+ year with knowledge graph
technologies.
- Technical Expertise:
- Generative AI:
- Proven experience building AI solutions using advanced prompt
engineering (Chain of Thought, Tree of Thought) and designing and
deployingRAG pipelines
- Experience with validation of LLM outputs and reduction of
hallucinations
- Knowledge ofAgentic AI architecture, and knowledge graph
integrationwith LLMs (e.g., GraphRAG, ontology-driven prompt
engineering, hybrid reasoning systems).
- Hands-on work withvector databases(Pinecone, Chromadb) and
frameworks likeLangChain/LlamaIndexfor orchestration.
- Classical Machine Learning:
- Strong foundation insupervised/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 inPython,PyTorch/TensorFlow, and ML libraries
(Scikit-learn, Hugging Face Transformers).
- Production experience withAWS/GCP(SageMaker, S3, Lambda)
- Demonstrated experience building data pipeline to process
structured and unstructured data sources, data cleansing/prep for
analysis
- Demonstrated experience with code repositories and
build/deployment pipelines, specifically Jenkins and/or
Git/GitHub/GitLabDesired Experiences:
- Education: MS/PhD in Computer Science, Data Science,
Statistics, Physics, Mathematics, or related quantitative
field.
- GenAI Experience
- Experience with LLM fine-tuning(LoRA, PEFT), andmulti-agent
systems(e.g., AutoGen, CrewAI).
- Experience withontology designfor domain-specific GenAI
applications (e.g., finance, healthcare).
- Knowledge Graph & GenAI Synergy:
- Buildingdynamic knowledge graphsfrom unstructured data (e.g.,
LLM-generated content) and using them for
retrieval/validation.
- Experience withontology designfor domain-specific GenAI
applications (e.g., finance, healthcare).
- Classical ML + GenAI Hybridization:
- Using classical ML forbias detection,anomaly monitoring,
orperformance optimizationin GenAI workflows.
- Experience with image processing models such as Coco, CLIP,
ResNet or comparable models
- Hybrid modeling (e.g., combining classical ML and GenAI)
- Advanced Tools:
- Graph ML: NetworkX, PyTorch, Graph Neural Network (GNN).
- Experience with MLOpstools (Docker, Kubernetes, MLflow).
- Knowledge & experience with microservices, service mesh, API
development and test automation
- Experience withgraph databases(Neo4j, AWS Neptune)
- Experience with Search/Retrieval: ElasticSearch, AWS
OpenSearch, or semantic search architectures.
- Research Mindset:
- Publications or open-source contributions in AI/ML (e.g.,
knowledge graph-enhanced LLMs, causal ML).Skills
- Strong customer-centric problem-solving mindset
- Ability to translate business ideas into analytics models that
have major business impact
- Demonstrated experience working with multiple stakeholders
- Demonstrated communication skills, e.g. explaining complex
technical issues to more junior data scientists, in graphical,
verbal, or written formats.
- Comfortable working with ambiguity (e.g. imperfect data,
loosely defined concepts, ideas, or goals)
- Demonstrated experience developing tested, reusable and
reproducible work.
- Transparently documenting code and methodologiesFannie Mae is a
flexible hybrid company. We embrace flexibility for our employees
to work where they choose, while also providing office space for
in-person work if desired. At times, business need may call for
on-site collaboration, which means proximity within a reasonable
commute to your designated office location is preferred unless job
is noted as open to remote.Fannie Mae is an Equal Opportunity
Employer, which means we are committed to fostering a diverse and
inclusive workplace. All qualified applicants will receive
consideration for employment without regard to race, religion,
national origin, gender, gender identity, sexual orientation,
personal appearance, protected veteran status, disability, age, or
other legally protected status. For individuals with disabilities
who would like to request an accommodation in the application
process, email us at careers_mailbox@fanniemae.com.The hiring range
for this role is set forth on each of our job postings located on
Fannie Mae's Career Site. 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 employee's physical, mental,
emotional, and financial well-being.
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Keywords: The Fannie Mae, Washington DC , Senior Data Scientist - AI Developer (Flexible Hybrid), IT / Software / Systems , Washington, DC
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