Data Scientist (SIE)

TL;DR

Data Scientist (SIE): Designing, developing, and implementing statistical techniques, ML algorithms, and predictive models for advanced analytics in edge solutions with an accent on exploratory analysis of complex high-dimensional datasets and AI/ML applications. Focus on processing technical data like CAD models, anomaly detection, time series analysis, and creating data visualizations and dashboards for insights.

Location: Hybrid in Saint Paul, MN. Requires U.S. citizenship and active U.S. national security clearance (or ability to obtain one). Travel to customer sites and other offices may be required.

Salary: 105,600 - 127,100 USD per year (Saint Paul, MN)

Company

Mission-driven technology company focused on national security, building advanced sensors, autonomous systems, mission command software, AI-enabled training, simulation, and logistics tools for DoD, allies, and critical industries.

What you will do

• Lead design, development, and implementation of statistical techniques and ML algorithms.
• Write clean, efficient code and apply best practices in data science workflows.
• Research AI/ML applications, align efforts with development and government teams.
• Prepare technical documentation for algorithms and ensure accuracy.
• Collaborate with data scientists, software engineers, and end users to deliver insights.
• Integrate advanced tools and methodologies to improve efficiency.

Requirements

• U.S. citizenship and ability to obtain/maintain U.S. national security clearance.
• Bachelor's in Computer Science, Statistics, Mathematics, Engineering, or related field.
• At least 2 years in data science or related, analyzing system performance and time series data.
• Proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, relational databases.
• Strong statistical analysis, forecasting, anomaly detection; data visualization (Tableau, Power BI, Grafana).
• ML fundamentals; excellent problem-solving, analytical, and communication skills.

Nice to have

• Experience with CAD models, technical datasets, ML models (classification, regression, etc.).
• Stream processing, cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch).
• Git, Docker, Kubernetes, data streaming (Kafka, etc.), aerospace/defense industry knowledge.

Culture & Benefits

• Hybrid work with in-office collaboration and flexible telework (supervisor approval).
• Paid Time Off, company holidays.
• Medical, dental, vision insurance; optional HSA/FSA; life/disability insurance.
• 401k matching, Employee Assistance Program.