Data Scientist for Energy, Environment and Infrastructure Consulting
5 days ago
At Exponent, we're a premium engineering and scientific consulting firm with a unique blend of expertise to tackle our clients' most complex challenges. Our vision is to empower clients with innovative solutions that create a safer, healthier, more sustainable world.
Job DescriptionWe're seeking a highly skilled Data Scientist to join our Data Sciences Practice in Los Angeles, CA. In this role, you'll work closely with our team to help clients solve urgent, high-profile technical problems across various industries, including consumer electronics, utilities, and life sciences.
- Support a range of consulting activities related to large-scale network problems involving energy, environment, and infrastructure, including model development, data analysis, and visualization.
- Develop cloud-based storage and computation solutions, including client-facing visualizations of key decision metrics.
- Actively solve technical and logistical problems in a fast-paced environment.
This position requires strong technical skills and experience in two or more areas: data/software product development, spatial analysis, engineering data pipelines, or software verification and validation. Proficiency in Python, R, C++, SQL, and Linux is also essential.
Required Skills and QualificationsM.S. in Statistics, Computer Science, or a related engineering/scientific field (such as Applied Mathematics, Bioinformatics, Civil Engineering, Electrical Engineering, Systems Engineering, or Physics).
- Demonstrated experience and expertise in two or more areas: data/software product development, spatial analysis, engineering data pipelines, or software verification and validation.
- The desire to work with a varied set of clients and Exponent teams on projects that integrate diverse subject matter expertise with data science capabilities.
- Proficiency with two or more programming languages, including Python, R, C++, SQL, and Linux.
- Prior experience with energy, environment, and infrastructure-related projects is preferred.
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