Opportunity

The Role
We’re looking for a Senior Data Scientist with strong skills in simulation modeling, mathematical optimization, and sensor data analysis. This is a hands-on, high-impact role where you will develop analytical solutions for real-world defense scenarios — from optimizing aircraft maintenance schedules to analyzing live sensor data from naval vessels.
You’ll be joining a cross-functional team that builds scalable, data-driven products supporting mission readiness and capability management. If you enjoy combining discrete-event simulation, CPLEX optimization, and sensor analytics to answer hard operational questions, this job will suit you well.

Meaningful Work in a Mission Driven Environment

Key Responsibilities:

Simulation Modeling

• Design and develop discrete-event simulations using SimPy (or similar) to model logistics chains, maintenance workflows, and operational bottlenecks.
• Build simulation components that reflect real-world systems, allowing for stress testing and what-if scenarios.

• Build and solve optimization models using IBM CPLEX.
• Translate complex operational needs — such as scheduling, resource allocation, or planning — into mathematical formulations.
• If you’ve used Gurobi or other solvers before, that's fine — but you’ll need to work with CPLEX here.

• Analyze high-volume, high-frequency sensor data from military platforms (air, land, sea).
• Extract signals, detect anomalies, and engineer features for predictive modeling.
• Combine time-series analytics with simulation and optimization outputs to inform decision-making.

• Write clean, modular Python code with attention to performance and reproducibility.
• Collaborate with data engineers, full-stack developers, and domain experts to productionize your models.
• Share knowledge across teams and contribute to internal tooling and frameworks.

What You Bring

What We’re Looking For/ Required Skills

• 5+ years of experience in Data Science, Operations Research, or a similar role.
• Strong coding skills in Python, including libraries like pandas, NumPy, matplotlib, scikit-learn.
• Solid experience with SimPy or any other discrete-event simulation library or tool.
• Practical experience formulating and solving optimization models with IBM CPLEX (knowledge of other solvers is welcome, but CPLEX is what we use).
• Experience working with sensor or time-series data in an applied setting.
• Strong problem-solving mindset — you enjoy turning ambiguous situations into concrete analytical approaches.

• Background in logistics, maintenance planning, systems engineering, or defense operations.
• Experience with containerized development (Docker) or distributed data tools (e.g., Apache Spark).
• Exposure to digital twins, operational dashboards, or predictive maintenance applications.
• Familiarity with working in secure or regulated environments (defense, aviation, etc.).

Contact

Exited and ready to explore how you could fit in? 
Let our HR team know and send your CV to [email protected]
we are thrilled to get to know you!