At 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 impact the future of the housing industry while being part of an inclusive team thriving in an energizing, flexible environment. Here, you will grow your career and help create access to fair, affordable housing finance.
Job DescriptionIn this compelling leadership position, you will plan and direct business unit operations and the work of a team who produce advanced analytics algorithms, AI techniques and innovative data science solutions, AI-enabled automation, and predictive modeling to drive the success of strategy implementation. You will ensure team members are knowledgeable in data mining and data analysis methods, adept with large data science, Artificial Intelligence, causal AI and Generative AI techniques, computational programing capabilities, practical problem-solving skills, and possess the ability to articulate solutions to non-technical consumers or partners. As the director, you will develop partnerships across the data engineering and data management teams, and external or created data sources to apply data mining techniques in preparation for analysis or use of enterprise data assets.
THE IMPACT YOU WILL MAKE
The Director of Data Science & Artificial Intelligence (AI) 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:
THE EXPERIENCE YOU BRING TO THE TEAM
Minimum Required Experiences
Desired Experiences
Master degree or PhD in computer science, Math, Statistics, engineering, physics or related field is preferredDemonstrated success in developing and deploying AI-driven solutions and models, particularly within the Financial or professional services sectors.Profound understanding of AI and advanced analytics technologies, coupled with the ability to evaluate their feasibility.Ideally, 10+ years of experience in Machine Learning, delivering complex prototyping solutions to production.Extensive proven, hands-on experience in data science. Expert-level experience with Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG).Extensive experience with advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, time-series analysis, statistical process control, are preferredPractical applications of machine learning techniques such as Clustering, Logistic Regression, CART, Random Forests, SVM or Neural Networks.Expert-level knowledge of deep learning frameworks such as TensorFlow, PyTorch, and other open sources libraries / APIs or similar. Strong technical and problem-solving skills and evidence of continuous learning in the analytics fieldBreadth and depth of knowledge in the application of statistical and/or digital methods to solve business problemsProficiency with Python and basic libraries for machine learning. Ability to visualize & synthesize results. Full stack experience building GenAI solutions; Large language models, language transformers (BERT, RoBERTa) data prep & vectorization, embedding/chunking, prompting, search/summary/RAG/finetuning.Experience with deep learning (e.g., CNN, RNN, LSTM) methods.Experience building NLP and NLG tools and a wide range of LLMs (Llama, Claude, OpenAI, etc.), LoRA, LangChain, RAG, LLM Fine Tuning and PEFT are preferred.Demonstrated skills with Jupyter Notebook, AWS Sagemaker, or Domino Datalab or comparable environmentsPassion for solving complex data problems and generating cross-functional solutions in a fast-paced environmentTools
Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets.Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment.Expertise in popular machine learning algorithms and libraries such as TensorFlow, PyTorch, and Keras.Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data.Strong proficiency in programming languages such as Python, R, and SQL, crucial for data manipulation and algorithm development.In-depth knowledge of cloud computing environments such as AWS, Azure, or Google Cloud Platform, particularly their AI and data analytics services.Experience with database management and querying tools, including traditional SQL databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Elastic Search).Familiarity with Amazon Bedrock, AmazonQ, or Google Vertex or Microsoft AI services is preferedFamiliarity with DevOps practices and tools (e.g., Jenkins, Docker, Kubernetes) for efficient deployment of AI solutions.Understanding of MLOps principles to streamline the machine learning lifecycle from experimentation to production.Knowledge of security protocols and compliance standards relevant to data privacy and AIAdditional InformationThe future is what you make it to be. Discover compelling opportunities at careers.fanniemae.com.
Fannie 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 [email protected].
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. See more here.