RELOCATION ASSISTANCE: No relocation assistance available

CLEARANCE TYPE: None

TRAVEL: Yes, 10% of the Time

Description

At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history.

Northrop Grumman Insights & Intelligence (i2) is seeking a Data Scientist to join Northrop Grumman’s Finance AI & Analytics organization.  This position will support the Business Management function, and the selected candidate will report to the Manager, Finance AI & Analytics. The location for this position is Falls Church, VA with the opportunity for a 100% virtual/telework arrangement. 

At Northrop Grumman, Finance 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 Finance 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 management 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 Mentor junior team members by providing guidance on best practices in data science Stay abreast of industry trends and methodologies and contribute innovative ideas to drive business value 

Basic Qualifications: 

PhD with 1 years of related professional experience OR Master’s degree and 3 years of related professional experience OR bachelor’s degree and 5 years of related professional experience Must have deep foundational knowledge of statistical modeling and machine learning concepts Must have expertise with Python (at least 4 years) Must have proficiency with data transformation using SQL or similar data querying language Must have experience using version software control (e.g. git) with a team of collaborators Must have experience using cloud-based data science tools – i.e. AWS, Azure, DataBricks, Spark/PySpark  Fluency in translating business problems into questions that can be answered via analytic methods  Experience collaborating on projects with multiple teams, managing relationships, and communicating findings to audiences 

Preferred Qualifications: 

Degree in a quantitative field (engineering, mathematics, statistics, computer science, etc.) is preferred Experience with Monte Carlo simulation, time series modeling, or probabilistic modeling Proven experience putting models into productionExperience interfacing and presenting to executive audiencesExperience with finance- or business management-related data

Primary Level Salary Range: $113,900.00 - $187,900.00

The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions.

Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business.

The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates.

Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit http://www.northropgrumman.com/EEO. U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.