Chief Cost Data Scientist and Principal Investigator

INNOVIM•,

6d•$185,000 - $225,000•Hybrid

About The Position

This position supports a potential Department of the Air Force opportunity and is contingent upon contract award, final Government requirements, and candidate qualification and clearance verification. This posting does not represent an offer of employment and does not imply that a contract has been awarded or that any offeror has been selected. IDS is building the technical leadership for a federal applied research program in acquisition cost analytics. The Chief Cost Data Scientist is the contractor senior technical authority for the entire effort: enterprise architect for the customer cloud cost data environment, technical lead for quality and consistency across every task and deliverable, and primary strategic advisor to the customer technical director on data strategy, technology insertion, and analytical innovation. This is not a conventional data science management role. The position requires genuine depth on both sides of a rare combination: defense cost estimating and applied machine learning research. Candidates who have one without the other will not meet the threshold.

Requirements

Bachelor of Science or Bachelor of Arts from an accredited institution.
Minimum ten years as a data scientist.
Minimum five years in cost estimating or cost analysis.
Minimum five years performing projects of comparable scope.
Leadership in data science: experience leading cross-functional teams of data scientists, data engineers, and data or cost analysts, and defining a data strategy aligned to organizational goals.
Demonstrated expertise integrating advanced data science capability with existing processes and technologies.
Demonstrated history of driving research and development initiatives in machine learning and artificial intelligence.
Knowledge and experience performing cost estimating and analysis on major defense systems, including typical work breakdown structures and standard cost data such as cost and software data reporting, operating and support data, earned value data, selected acquisition reports, and budget data.
Demonstrated experience developing cost estimating relationships and performing analogy estimating.
Exceptional communication skills, including translating complex analytical results into actionable recommendations for senior stakeholders.
Active Secret clearance.
United States citizenship required.

Nice To Haves

Advanced degree in a quantitative discipline strongly preferred.
Doctorate in statistics, operations research, economics, engineering, or a related quantitative field.
Published research record in cost estimating, applied statistics, or machine learning.
Experience with Databricks, Apache Spark, Python, R, and SQL in a governed cloud environment.
Prior support to a service cost agency, the Office of the Secretary of Defense, or a major defense acquisition program office.
Top Secret clearance with SCI eligibility.

Responsibilities

Serve as senior technical authority across all tasks, including technical oversight of all pipeline designs, analytical methods, deployed products, and subcontractor technical work.
Serve as enterprise architect for the customer cloud cost data environment: own architecture decisions, technology stack recommendations, and platform evolution, and approve contractor-level decisions within a tiered government decision framework.
Own experimental design, statistical governance, model selection policy, validation criteria, and reproducibility standards.
Make machine learning applicability determinations: decide where ML earns its place over transparent parametric methods, and document the sample size and data quality conditions under which each holds.
Identify and present technology insertion recommendations to the customer, stating the expected benefit, impact on existing pipelines and products, level of effort, and risk.
Serve as primary strategic advisor to the customer technical director, and work with the program manager to identify adoption barriers and integrate products into cost estimating workflows.
Ensure technical content quality, commonality, and configuration compliance across all tasks, and author or approve the technical research reports.
Drive research and development initiatives in machine learning and artificial intelligence, and translate complex analytical results into actionable recommendations for decision makers.