Senior Data Scientist AI Developer Flexible Hybrid
Senior Data Scientist AI Developer Flexible Hybrid
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1 Vacancy
Job Description
Fannie 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 Were 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 worlds 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 MAKE
The 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 nontechnical presentation materials to communicate complex ideas and solutions to business partners.
Qualifications :
THE EXPERIENCE YOU BRING TO THE TEAM
Minimum Required Experiences:
- Education: Bachelors degree in Computer Science Data Science Statistics Physics Mathematics or related quantitative field.
- Experience: 2 years in ML engineering including 2 years handson with Generative AI/LLMs and 1 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 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 ontologydriven prompt engineering hybrid reasoning systems).
- Handson work with vector databases (Pinecone Chromadb) and frameworks like LangChain/LlamaIndex for orchestration.
- Classical Machine Learning:
- Strong foundation 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 (Scikitlearn 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
- Demonstrated experience with code repositories and build/deployment pipelines specifically Jenkins and/or Git/GitHub/GitLab
- Generative AI:
Desired Experiences:
- Education: MS/PhD in Computer Science Data Science Statistics Physics Mathematics or related quantitative field.
- GenAI Experience
- Experience with LLM finetuning (LoRA PEFT) and multiagent systems (e.g. AutoGen CrewAI).
- Experience with ontology design for domainspecific GenAI applications (e.g. finance healthcare).
- Knowledge Graph & GenAI Synergy:
- Building dynamic knowledge graphs from unstructured data (e.g. LLMgenerated content) and using them for retrieval/validation.
- Experience with ontology design for domainspecific GenAI applications (e.g. finance healthcare).
- Classical ML GenAI Hybridization:
- Using classical ML for bias detection anomaly monitoring or performance optimization in 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 MLOps tools (Docker Kubernetes MLflow).
- Knowledge & experience with microservices service mesh API development and test automation
- Data Engineering:
- Experience with graph databases (Neo4j AWS Neptune)
- Experience with Search/Retrieval: ElasticSearch AWS OpenSearch or semantic search architectures.
- Research Mindset:
- Publications or opensource contributions in AI/ML (e.g. knowledge graphenhanced LLMs causal ML).
Skills
- Strong customercentric problemsolving 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 methodologies
Additional Information :
The future is what you make it to be. Discover compelling opportunities at careers.fanniemae.
Fannie Mae is a flexible hybrid company. We embrace flexibility for our employees to work where they choose while also providing office space for inperson work if desired. At times business need may call for onsite 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
The hiring range for this role is set forth on each of our job postings located on Fannie Maes 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 employees physical mental emotional and financial wellbeing. See more here.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
