Data Scientist for Economic Modeling

5 days ago


Durham, North Carolina, United States RTI International Full time
Our team at RTI International is working on various projects that aim to advance innovation and economic growth. As a data scientist, you will have the opportunity to work on challenging problems and develop innovative solutions using machine learning and data science techniques. You will collaborate with a diverse team of economists, policy analysts, and other experts to deliver high-quality research and analysis to our clients.

In this role, you will be responsible for designing, executing, and communicating data analysis and research studies. You will also contribute to the development of research, development, and innovation economic models, incorporating underlying datasets and understanding data availability and limitations. Additionally, you will develop post-processing routines for analyzing, reporting, and visualizing model outputs and maintain currency with key issues and concepts in innovation topic areas, including research policies and programs, R&D workforce policy, research assessment, research commercialization, and technology transfer.

This position offers a unique opportunity to work on cutting-edge topics and develop your skills in machine learning, data science, and economic modeling. If you are passionate about innovation and economic growth, and have a strong background in data science and machine learning, we encourage you to apply.

Responsibilities
Conduct literature reviews to identify best available data and/or best practices for data processing and analysis; Design, execute, and communicate data analysis and research; Lead the maintenance of core datasets to our analyses in replicable code and version-controlled repositories; Participate in and/or lead projects, tasks, and staff in a wide variety of technical activities including data pipeline development and orchestration, data wrangling/munging, data infrastructure, ETL processes, exploratory data analyses, DataOps, AI and machine learning, deep learning, natural language processing, microsimulation modeling, MLOps, generative AI and Large Language Models, computer vision, automation, cloud computing, social media analytics, privacy analytics, rapid prototyping, data visualization, and user-centered design;
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