Staff Data Science Engineer

SimSpace

Data Science Engineer at SimSpace developing machine-learning algorithms for cybersecurity. Collaborating on advanced AI-driven solutions in a hybrid work environment.

Posted 4/24/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesLead💰 $183,801 - $184,000 per yearWebsite

Tech Stack

Tools & technologies

Cyber SecurityDockerKubernetesNumpyPandasPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Design, implement, and deploy advanced mathematical and machine-learning algorithms to support cyber-range simulations.
Develop and maintain end-to-end AI/ML pipelines.
Construct and optimize numerical methods and computational models using Python, NumPy, SciPy, Pandas, and JAX/TensorFlow/PyTorch.
Architect scalable model-serving systems in Docker/Podman/Kubernetes.
Develop and integrate new AI-driven cybersecurity capabilities.
Author and maintain production-quality Python services.
Design, evaluate, and improve model performance using quantitative metrics.
Perform algorithmic research on emerging ML/AI/cyber methods.
Lead cross-team technical initiatives.
Mentor senior-level engineers and data scientists.

Requirements

What you’ll need

Ph.D. in Computational Mathematics, Computer Science, Applied Mathematics, or a closely related field.
1 year of experience in computational mathematics, scientific computing, machine learning, data science, or algorithm development.
Demonstrated experience applying machine-learning algorithms to datasets of at least 1 million observations or high-dimensional data.
Demonstrated experience developing scientific or ML software in Python using at least three of the following packages: NumPy, Pandas, SciPy, Matplotlib.
Demonstrated experience implementing machine-learning models using at least three of the following frameworks: PyTorch, TensorFlow, JAX, scikit-learn.
Demonstrated experience writing automated tests for ML or scientific code using at least two of the following: unittest, pytest, hypothesis.
Demonstrated experience building and deploying containerized applications using at least one of the following: Docker, Podman, Kubernetes.
Demonstrated experience producing documented research or production-quality software artifacts.
Demonstrated experience applying computational mathematics methods to design or evaluate algorithms or models, with documented quantitative results.
Demonstrated understanding of statistics, computational complexity and performance, parallelization, databases, optimization, linear programming, hypothesis testing.

Benefits

Comp & perks

In-house training
Internal and external learning platforms
Cyber conferences
Industry events
Dedicated time for skill development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningmathematical algorithmscomputational modelsnumerical methodsPythondata sciencealgorithm developmentautomated testingstatisticsoptimization

Soft Skills

leadershipmentoringcross-team collaboration

Certifications

Ph.D. in Computational MathematicsPh.D. in Computer SciencePh.D. in Applied Mathematics