Cost Engineer/Data Scientist (TS clearance required)

Lockheed Martin•Sunnyvale, CA

19h•Onsite

About The Position

Space is a critical domain, connecting our technologies, our security and our humanity. While others view space as a destination, we see it as a realm of possibilities, where we can do more — we can innovate, invest, inspire and integrate our capabilities to transform the future. At Lockheed Martin Space, we aim to harness the full potential of space to cultivate innovation, reduce costs, and push the boundaries of what technology can achieve. We’re creating future-ready solutions, focusing on resiliency and urgency through our 21st Century Security® vision. We’re erasing boundaries and forming partnerships across industries and around the world. We’re advancing spacecraft and the workforce to fuel the next generation. And we’re reimagining how space can connect us, ensuring security and prosperity. Join us in shaping a new era in space and find a career that's built for you. The Predictive Analytics and Cost Engineering (PACE) team is a data science team that combines technical engineering attributes and financial information to create data-driven cost estimates for program capture and support. The PACE team collects, normalizes and maps data to a standard work breakdown structure (WBS) to perform data analytics for internal and external customer support and deliverables. As part of the Finance and Business Operations (F&BO) organization, this team also works closely with Engineering and Technology (E&T), Strategy and Business Development (S&BD), Program/Proposal Management and Leads, Executive leadership and external customers. In particular, this position would be in support of significant programs/capture efforts in the National Security Space (NSS) line of business (LOB). This may also involve proposal and/or data analytics and cost estimating tool development or enhancements. The role may include working on affordability analysis, life cycle cost developments, cost data analytics, forecasting cost and schedule, data collection and normalization, and design to cost. The candidate selected will be asked to analyze multiple data sets to build engineering models, synthesize results, perform decision analysis, and communicate findings with engineering colleagues and internal decision makers.

Requirements

Bachelor's or Master's degree or equivalent years of experience in lieu of degree
Top Secret Clearance
Strong communication and interpersonal skills
Exceptional critical thinking and problem-solving abilities
Detail-oriented with ability to multitask, prioritize and balance multiple tasks at once
Comfortable navigating technical or cost data with the intent of understanding the relationship between them when working a task and/or presenting results
High degree of accountability and responsibility with the ability to be a self-starter
Experience with and understanding of one or more of the following: cost model development, data collection and normalization, data science, data analytics, systems engineering/architecture, spacecraft engineering fields, and/or finance

Nice To Haves

Master's degree in Math, Operations Research, Engineering, Finance, or related field or equivalent years of experience
Experience with Python, Visual Basic for Applications (VBA), MS SQL, and/or Tableau
Experience working with cost models, predictive analytics, or decision analysis
Knowledge of financial systems, analysis, statistics, etc.
Experience working within the space systems industry
Knowledge of data management systems and/or data science
Ability to communicate technically oriented material to broader team
Familiarity with proposal development and/or the government acquisition process
Strong team collaboration and leadership skill
5+ years of related experience

Responsibilities

Coordinate with Engineering, Business Development, Program Finance, Estimating, Proposal Management, and ICE around cost estimates.
Be comfortable supporting development of AI/ML tools collaborating with the above organizations
Present briefings to colleagues, senior staff, and executives.
Develop data-driven cost estimates for proposal efforts that are parametrically derived.
Normalize cost and technical data.
Become knowledgeable and responsible to answer questions around cost estimates and cost drivers.