Role overview
- Develop and evaluate machine learning models using Python to analyze time-series and telemetry data.
- Perform data exploration, feature engineering, and preprocessing on structured and semi-structured datasets.
- Develop Physics-informed models based on the known relationships of signals for systems with low historical data available.
- Implement algorithms for anomaly detection, predictive modeling, and trend analysis in operational data.
- Support model validation, performance evaluation, and documentation.
- Contribute to the deployment of models into production and embedded environments in coordination with engineering teams.
- Collaborate with data visualization and software teams to integrate model outputs into dashboards and decision-support tools.
- Document methodologies, assumptions, and results for technical and non-technical stakeholders.
- Stay current with emerging machine learning techniques and apply best practices to ongoing projects.
- Perform other duties as assigned.
Basic qualifications
- Master’s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field with 0 years of experience, or Bachelor’s degree in a related field with 2+ years of relevant experience (or equivalent experience in lieu of a degree).
- Proficiency in Python for data analysis and machine learning.
- Experience with common machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow, or similar).
- Familiarity with time-series data, telemetry, or sensor-based datasets.
- Working knowledge of data analysis tools such as NumPy, Pandas, and SciPy.
- Ability to communicate technical concepts clearly in both written and verbal form.
- Strong analytical thinking and problem-solving skills.
- Must be a U.S. Citizen with the ability to obtain and maintain a security clearance.
Preferred qualifications
- Experience applying machine learning to predictive maintenance, health monitoring, or operational analytics on time-series data systems.
- Exposure to model deployment concepts (e.g., batch pipelines, APIs, or edge/embedded environments).
- Familiarity with cloud platforms or big data environments.
- Experience working in a government or DoD context.
- Familiarity with the relationship between engine signals and performance.
- Knowledge of version control (e.g., Git) and collaborative development workflows.
Benefits
- Health benefits
- Medical
- Dental
- Vision
- Basic life with AD&D
- Short term disability
- Long term disability
- Ancillary (Voluntary life with AD&D, accident, critical illness, hospital, and pet)
- Spending accounts (HSA, FSA, and DCFSA)
- Paid time off
- Holidays
- 401(k) (including automatic company contribution)
- Tuition reimbursement
- Leaves (Parental, pregnancy, and military)
- Potential annual bonus
Tags & focus areas
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