Data Scientist analyzing claims data, optimizing processes and collaborating across departments at Allianz Spain. Utilizing statistical techniques and developing predictive models for operational efficiency.
About the role
- Senior AI and Machine Learning Research Engineer at CACI applying machine learning and statistics to solve complex RF problems and design robust data pipelines. Required to have a strong mathematical background and experience in cloud-based solutions.
Responsibilities
- Apply machine learning, statistics, to develop algorithms to solve challenging problems
- Leverage strong foundation in machine learning, data science, and signal processing to solve complex challenges in the RF domain
- Design and build data pipelines, including ETL processes, data warehousing solutions, and optimizing workflows for large-scale data processing
- Hands-on experience with cloud-based infrastructure for deploying ML solutions, including containerization, orchestration, and CI/CD pipelines for model deployment
- Programming expertise in Python and SQL, with experience using data engineering frameworks and ML libraries
- Establish ML governance practices, including version control for datasets and models, experiment tracking, model monitoring, implementing reproducible research principles
Requirements
- Master’s degree in quantitative field with mathematical underpinnings
- At least 5 years’ experience
- Experience developing models
- Strong background in machine learning, mathematics and statistics
- Comfortable using Linux operating systems and commonly used Linux utilities
- Must be a US Citizen with the ability to obtain, maintain and/or transfer the required security clearance
- Must have active Top Secret Clearance with the ability to obtain SCI with Polygraph
- Ph.D. in computer science, computer engineering, or machine learning, Statistics, applied mathematics or Physics (Desired)
- Experience applying machine learning to signal processing and/or other time-series data analysis applications (Desired)
Benefits
- Healthcare
- Wellness
- Financial
- Retirement
- Family support
- Continuing education
- Time off benefits
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