Overview:
LMI is seeking a seasoned Data Scientist to support 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: Innovation at the Pace of Need™
At LMI, we’re reimagining the path from insight to outcome at the new speed of possible. Combining a legacy of over 60 years of federal expertise with our innovation ecosystem, we minimize time to value and accelerate mission success. We energize the brightest minds with emerging technologies to inspire creative solutioning and push the boundaries of capability. LMI advances the pace of progress, enabling our customers to thrive while adapting to evolving mission needs.

Responsibilities:

• Collaborate actively within a team of data scientists to rapidly design and deploy machine learning meta models, capturing complex scenarios across an extensive array of weapon system components
• Apply Design of Experiments (DOE) and meta modeling techniques to accurately represent simulation outputs
• Craft and deploy 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
• Advance the automation, efficiency, and precision of meta modeling and optimization solutions by contributing innovative approaches and enhancements
• Collaborate closely with data engineers, UI developers, and domain experts to refine and integrate data science methodologies into an adaptive software ecosystem
• 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

Qualifications:

• Bachelors degree in Data Science, Operations Research, or a related field, supplemented by relevant work experience
• 1-3 years’ experience in a data science capacity
• Experience with supervised/unsupervised ML methodologies
• SQL experience preferred, not required
• Python experience required
• Databricks experience preferred, not required
• GitHub, CI/CD workflow experience desired
• Proficiency in Agile development methodologies
• Strong background in Python, Spark notebooks, and cloud-based environments like Databricks
• Experience with Python libraries such as Scikit-learn
• Demonstrated ability to use MLflow and similar tools
• Robust analytical, conceptual, and problem-solving skills
• Active DoD Secret clearance required; Top Secret clearance preferred

• Collaborate actively within a team of data scientists to rapidly design and deploy machine learning meta models, capturing complex scenarios across an extensive array of weapon system components
• Apply Design of Experiments (DOE) and meta modeling techniques to accurately represent simulation outputs
• Craft and deploy 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
• Advance the automation, efficiency, and precision of meta modeling and optimization solutions by contributing innovative approaches and enhancements
• Collaborate closely with data engineers, UI developers, and domain experts to refine and integrate data science methodologies into an adaptive software ecosystem
• 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 challenge