Data Scientist- Hybrid in Reston VA

Job: Data Scientist

Location: Hybrid in Reston VA

Duration: 12+Months

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? 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.

Minimum Qualifications:
Work or educational background in one or more of the following areas: machine learning, computational linguistics, deep learning, ratification intelligence, data science and/or data analytic, generative AI, symbolic AI, causal AI, operations research, computer science, Mathematics, business analytics, or knowledge management.
Demonstrated experience programming with R/Python, Linux, and Spark in AWS cloud environment, or knowledge and algorithmic design experience in Python (3+ years)
Proficient with Amazon AWS Sagemaker, Jupyter Notebook and Python Scikit, Deep Learning, Machine Learning tools such as TensorFlow
Experience with image processing models such as Coco, CLIP, ResNet or comparable models
Demonstrated experience with machine learning techniques including natural language processing, and Large language Models (GPTv4-o1, o3, OpenAI APIs, Llama, Claude, etc).
Experience developing AI agents and development proficiency using agentic programming
Proficient in Natural language processing (NLP) and Natural language generation (NLG) including prior projects in any of the following categories: top modeling of text, sentiment analysis of text, part of speech tagging, Name Entity Recognition (NER), Bag of Words, text extraction
Experience building and working with any of these components: Vector DB, BERT, RoBERTa (or comparable tools), Spacy, LLM and GenAI tools. Experience with LoRA, LangChain, RAG, LLM Fine Tuning and PEFT, Knowledge Graphs.
Strong skills in developing GraphRAG, Chain of Thought (CoT), Tree of Thought (ToT), Reinforcement learning and AI development architectures with Human-in-the-Loop (HITL
Demonstrated experience with SQL and any relational database technologies, such as Oracle, PostgreSQL, MySQL, RDS, Redshift, Hadoop EMR, Hive, etc.
Demonstrated experience processing structured and unstructured data sources, data cleansing, data normalization and prep for analysis
Demonstrated experience with code repositories and build/deployment pipelines, specifically Jenkins and/or Git/GitHub/GitLab.
Demonstrated experience using Tableau, or Kibana, Quicksights or other similar data visualizations tools.
Very comfortable working with ambiguity (e.g. imperfect data, loosely defined concepts, ideas, or goals)
Qualifications & Requirements
Education: MS in Computer Science, Statistics, Math, Engineering, or related field, PhD preferred
3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
1+ year of experience specifically with deep learning (e.g., CNN, RNN, LSTM)
1+ year of experience building NLP and NLG tools.
Experience with wide range of LLMs (Llama, Claude, OpenAI, Cohere, etc.), LoRA, LangChain, RAG, LLM Fine Tuning and PEFT are preferred.
Demonstrated skills with Jupyter Notebook, AWS Sagemaker, or Domino Datalab or comparable environments
Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment
Knowledge in Python and SQL, object oriented programming, service oriented architectures
Strong scripting skills with Shell script and SQL
Strong coding skills and experience with Python (including SciPy, NumPy, and/or PySpark) and/or Scala.
Knowledge and implementation experience with NLP techniques (topic modeling, bag of words, text classification, TF/IDF, Sentiment analysis) and NLP technologies such as Python NLTK, or Spacy or comparable technologies
Knowledge and implementation experience with statistical and machine learning models (regression, classification, clustering, graph models, etc.)
Preferred Qualifications
Hands on experience building models with deep learning frameworks like Tensorflow, Keras, Caffe, PyTorch, Theano, H2O, or similar
Experience with LLM Agents, Agentic programming
Experience with search architecture (for instance: Solr, ElasticSearch, AWS OpenSearch)
Experience with building querying ontologies such as Zeno, OWL, RDF, SparQL or comparable are preferred
Knowledge & experience with microservices, service mesh, API development and test automation are preferred
Demonstrated experience using Docker, Kubernetes, and/or other similar container frameworks are preferred
Strongly prefer a PhD in math, computer science stat or comparable field with experience in data science, AI development and deep learning, advanced analytics
Additional Job Qualifications:
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.
Demonstrated experience developing tested, reusable and reproducible work.
Transparently documenting code and methodologies.
Ability to work in Agile, Lean and rapid development processes