Northrop Grumman is seeking a Data Scientist to join our Business Development AI & Analytics organization. This position will support the Business Development function, and the selected candidate will report to the Manager, Business Development AI & Analytics. The location for this position is Falls Church, VA with the opportunity for a hybrid or telework arrangement.
At Northrop Grumman, Business Development AI & Analytics is a core domain within our Insights & Intelligence (i2) organization. As part of our Chief Information & Digital Office (CIDO), i2 works with all enterprise domains and businesses to drive our data, analytics & AI transformation.
Insights and Intelligence (i2) Solutions is a team of data scientists, behavioral research scientists, insight analysts, data engineers, and technologists who use science to drive insight and data strategy within the business. As a member of Business Development AI & Analytics, you will be responsible for guiding the organization with strategic analysis and providing meaning behind data.
As a data scientist, you will be responsible for developing and scaling models to approximate our complex business and potential future scenarios to ultimately help answer “what if…?” questions. You will be curious, detail-oriented, and ethically conscious. You are a creative problem-solver who can determine appropriate methodologies to apply to unique data applications. You think architecturally about the business development domain to comprehensively solve Enterprise problems at scale. You want to drive positive change and are candid and collaborative in taking on our most difficult analytics projects as well as the process and culture changes that accompanies them.
Responsibilities:
Develop statistical and machine learning models with a modeling & simulation lens to help quantify and reduce future uncertainty across various scenarios
Build well-structured and understandable code to enable smooth collaboration across the team and successful model deployment
Serve as a trusted technical expert who can offer informed guidance on methodology or technology decisions and communicate core requirements to our technology teams
Stay abreast of industry trends and methodologies and contribute innovative ideas to drive business value
Utilizing exceptional interpersonal and communication skills to present complex models or analyses to business partners
Basic Qualifications:
Must have a Bachelor’s degree with a minimum of 5 years of relevant professional experience OR a Master’s degree with a minimum of 3 years of relevant professional experience OR a PhD with a minimum of 1 year of relevant professional experience.
Must have a deep foundational knowledge of statistical modeling and machine learning concepts
Must have at least 3 years of experience with Python
Must have proficiency with data transformation using SQL or similar data querying language
Must have experience with visualization tools or libraries, such as Streamlit, Plotly, or Tableau
Must have experience using version software control (e.g. git) with a team of collaborators
Must have experience using cloud-based data science tools including AWS, Azure, DataBricks, Spark/PySpark
Must have fluency in translating business problems into questions that can be answered via analytic methods
Must have experience collaborating on projects with multiple teams and communicating findings to both technical and non-technical audiences
Preferred Qualifications:
Degree in a quantitative field (engineering, mathematics, statistics, computer science, etc.) is preferred
Experience with large language models (LLMs) or retrieval-augmented generation (RAG) techniques
Experience with Monte Carlo simulation, time series modeling, or probabilistic modeling
Proven experience putting models into production
Experience communicating insights through data-journalism and presenting to executive audiences
Experience with Business Development or Strategy related data (Customer Relationship Management (CRM) tools such as Salesforce and CRM Analytics)
Experience with analyzing intel from various aerospace and defense industry data sources such as DACIS, Jane’s, SAM.gov