Note: The job is a remote job and is open to candidates in USA. Trident Systems develops engineering solutions for aerospace electronic systems and supports DoD, Intelligence Community, and civil space customers. The Senior Data Scientist will develop, evaluate, and deploy machine learning models using Python and operational telemetry data for predictive maintenance, anomaly detection, forecasting, and decision support. The role also involves collaborating with engineering and visualization teams to transition analytical solutions into operational environments.
Responsibilities
- 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
- Utilize natural language processing and probabilistic modeling to extract data from maintenance records
- 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
- Ability to support travel or off-site work, as needed
- Perform other duties as assigned
Skills
- 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)
- Experience with natural language processing techniques and toolchains
- 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
- Experience applying machine learning to predictive maintenance, health monitoring, or operational analytics on time-series data systems
- Experience applying advanced techniques to extract meaningful data from bulk maintenance records to inform future maintenance actions
- 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
- 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 company match)
- Tuition reimbursement
- Leaves (Parental, maternity, and military)
- Annual discretionary bonus (for eligible roles)
- Potential annual bonus
Company Overview