60 applicants

Company

RTI International · 1 day ago

Data Scientist, Innovation Programs and Policy

United States

Full-time

Remote

Mid Level

$115K/yr - $143K/yr

3+ years exp

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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

Experience with modern open-source programming languages used in data science, such as: Python, SQL, R.

Lead the maintenance of core datasets to our analyses in replicable code and version-controlled repositories (i.e. via GitHub)

Participate in and/or lead projects, tasks, and staff in a wide variety of technical activities: data pipeline development and orchestration, data wrangling/munging, data infrastructure, ETL (Extract, Transform, Load) processes, exploratory data analyses (EDA), DataOps, AI and machine learning, deep learning, natural language processing (NLP), microsimulation modeling, MLOps, generative AI and Large Language Models (LLMs), computer vision, automation, cloud computing, social media analytics, privacy analytics, rapid prototyping, data visualization, and user-centered design.

Ability to develop ETL pipelines and conduct analyses using a wide variety of sources (e.g., relational databases, text and unstructured files, sensor data, image and video data, streaming data).

Contribute to the development of research, development and innovation economic models, incorporate underlying datasets and understand data availability and limitations.

Develop post-processing routines for analyzing, reporting, and visualizing model outputs.

Visualize data in clear and compelling graphics including dynamic implementations (e.g. in Tableau or R markdown).

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.

Work with a wide variety of data content and formats, including grant award data, research output data (such as patents, publications), economic data including industry, household, and national accounts information, global financial data, government statistical datasets for R&D and innovation.

Collaborate effectively with project team members, and with external scientists.

Manage workflow in a timely, realistic, and cost-effective manner to meet client expectations.

Contribute to grant, cooperative agreement, and contract proposals.

Present research methods and findings via technical reports, journal articles, and presentations.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data ScienceMachine LearningEconomic ModelingR ProgrammingPython ProgrammingSQLDeep LearningNatural Language ProcessingComputer VisionData VisualizationETL ProcessesGenerative AILarge Language ModelsData Pipeline DevelopmentJuliaData WranglingSimulation ModelingGrant Funding AnalysisNamed-Entity-RecognitionOptical Character RecognitionPredictive AnalysisGovernment R&D SupportBiomedical R&DScience & Technology Policy

Required

Master’s degree and three years of relevant work experience or a Bachelor’s degree and five years of relevant work experience.

Demonstrated experience collecting, processing, managing and analyzing data, including experience with and knowledge of best coding practices for one or more of the following: R, Python, Julia, or related programs.

Demonstrated proficiency with advanced analytics and data science techniques, such as: AI and machine learning, generative AI and Large Language Models (LLMs), deep learning, natural language processing (NLP), computer vision, optimization, and simulation modeling (e.g., agent-based models, microsimulation models).

Demonstrated interest in innovation, research & development programs or science & technology policy issues.

Excellent verbal and written communication skills, including ability to communicate complex issues to a wide range of audiences, and a track-record of publications and/or quantitative analytical outputs. If selected to interview for the position, writing samples will be required, preferably with a focus related to one of the topic areas above.

Preferred

Demonstrated experience analyzing grant funding data sets and grant funding outcomes.

Demonstrated experience with economic analysis of private R&D initiatives.

Demonstrated experience with Named-Entity-Recognition (NER), Optical Character Recognition (OCR, Tesseract), and transformer models.

Demonstrated experience developing and programming machine learning or other types of models for predictive analysis.

Experience working on topics related to government support for research & development, biomedical research & development, science & technology policy and workforce.