Senior Data Modeling & Lead Data Scientist - Clearance Required

LMI•Tysons, VA

About The Position

LMI is seeking a seasoned Lead Data Scientist to spearhead the development, testing, and deployment of machine learning (ML) models. These models are crucial for encapsulating extensive discrete event simulation data, aiding a critical supply chain risk program for the Department of Defense. LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed. Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Requirements

Masters degree in Data Science, Operations Research, or a related field, supplemented by relevant work experience
Minimum of 10 years’ experience in a data science capacity
Extensive experience applying Agile methodologies
Demonstrates expert-level skills in Python and Spark, with a strong command of cloud-based platforms such as Databricks, enhancing collaborative development and large-scale data processing
Deep knowledge and practical experience with delivering sophisticated data analysis and machine learning solutions using Python
Well-versed in using MLflow and comparable tools
Robust analytical, conceptual, and problem-solving skills
Active DoD Secret clearance required; Top Secret clearance preferred

Nice To Haves

Familiarity with Qlik, React or other data visualization platforms

Responsibilities

Direct a dynamic team of data scientists to swiftly develop and implement ML meta models that encapsulate numerous simulated scenarios across a vast inventory of weapon system components
Apply Design of Experiments (DOE) and meta modeling techniques to accurately represent simulation outputs
Adapt and enhance established, sophisticated supervised ML models employing tools such as Python, PySpark, and MLflow
Utilize meta models to facilitate optimization modeling, employing methods such as linear programming and heuristic approaches
Mentor and lead the team towards enhancing automation, efficiency, and accuracy of meta modeling and optimization solutions
Collaborate closely with data engineers, UI developers, and domain experts to refine and integrate data science methodologies into an adaptive software ecosystem
Collaborate closely with peer technical leads to identify priorities, risks and solutions
Operate proficiently within a Databricks environment, managing code development, testing, and deployment through notebooks
Manage data science initiatives, ensuring effective coordination and prioritization across multiple team engagements
Engage with cutting-edge data science techniques to address complex, large-scale data challenges