Director of Data Science & Artificial Intelligence (AI) - (Flexible Hybrid)
Company: Fannie Mae
Location: Washington
Posted on: November 14, 2024
Job Description:
Job Description
In 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:
- Lead a team of data scientist and AI developers, inspire
innovation and development of advanced AI solutions from inception
to production.
- Drive advancements in AI, while shaping the future of AI in
mortgage industry and supporting the company's mission.
- Ensure collaboration with product and/or business owners, data
engineers, and platform teams to align team objectives and group
strategy.
- Oversee the application of AI and data science techniques from
disciplines, such as computer science, computational science and
methods, statistics, econometrics, data optimization, and data
visualization. Ensure statistical modeling capabilities meet the
group's strategic needs.
- Direct and execute the deployment of AI capabilities,
Generative AI solutions, recommender systems, predictive analytic
capabilities to enhance the delivery of business applications and
support the integration of data and statistical models or
algorithms.
- Apply innovative practices in data science and AI research and
testing to product development, deployment, and maintenance.
- Direct the design of modeling applications to resolve complex
or unusual business problems.
- Ensure the team communicates complex ideas and solutions
effectively to division leadership through data visualizations,
technical documentation, and non-technical presentation
materials.
Qualifications
THE EXPERIENCE YOU BRING TO THE TEAM
Minimum Required Experiences
- 8 years of relevant experience in AI, data science, or related
fields, with a proven track delivering solutions to production
- Exceptional leadership skills, with experience in building,
mentoring, and guiding high-performing, diverse teams of data
scientists and AI professionals.
- Exemplary communication and stakeholder management skills,
adept at engaging with leadership and key stakeholders to drive
consensus and action.
- A spirit of scientific discovery, driven by a passion for
innovation to deliver results, balanced with a deep understanding
of risks and ethical considerations.
- 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.
- Bachelor's degree in computer science, Math, Statistics,
engineering, physics or related field or equivalent
experienceDesired Experiences
- Master degree or PhD in computer science, Math, Statistics,
engineering, physics or related field is preferred
- Demonstrated 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
preferred
- Practical 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 field
- Breadth and depth of knowledge in the application of
statistical and/or digital methods to solve business problems
- Proficiency 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 environments
- Passion 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 prefered
- Familiarity 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 AI
Additional Information
The future is what you make it to be. Discover compelling
opportunities at 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
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. See more -PandoLogic. Keywords: Data Science
Director, Location: Washington, DC - 20251
Keywords: Fannie Mae, Aspen Hill , Director of Data Science & Artificial Intelligence (AI) - (Flexible Hybrid), Executive , Washington, Maryland
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