Exponent is seeking an Applied Data Scientist to solve complex, applied problems in data engineering, analytics, and hands-on problem solving, particularly in healthcare, government contracting, and other high-impact engineering domains
Requirements
- Ph.D. in Computer Science, Physics, Applied Mathematics or a related engineering/scientific field OR M.S. plus 3+ years of industry experience in data science, applied machine learning, or data engineering after finishing the M.S. degree
- Proficiency in Python and scientific computing libraries (e.g., NumPy, Pandas, SciPy, scikit-learn)
- Experience with real-world data collection, cleaning, and analysis, including handling missing data, measurement error, and sensor calibration
- Familiarity with SQL databases, cloud platforms (AWS, Azure, or GCP), and version control systems
- Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) is a plus
- Strong practical engineering skills and ability to build robust, maintainable systems
Responsibilities
- Design and implement scalable data pipelines and analytical workflows across diverse domains
- Work with experimental and observational data, including sensor data, clinical records, and operational logs
- Apply statistical and machine learning techniques using input from engineering domain experts and information technology specialists
- Support data integration and transformation efforts across complex data ecosystems with a strong emphasis on error estimation and uncertainty quantification
- Collaborate with stakeholders to define data requirements and produce deliverables for projects
- Ensure data security and compliance with federal and industry standards
Other
- Recent M.S. graduates do not meet the requirement
- Proof of U.S. citizenship and the possession of or ability to obtain a U.S. DoD Security Clearance
- Strong communication skills and ability to work in cross-functional teams
- Ability to balance work and personal schedules
- U.S. citizenship is required for this position
