Associate R & D Data Scientist
Role details
Job location
Tech stack
Job description
The Associate R&D Data Scientist contributes to the planning, development, and execution of data science analyses for research and development projects within the ETS Research Institute. This role focuses on applying advanced data science, statistics, machine learning, and AI to make inferences and/or predictions from data. The position requires expertise in modern frameworks and cloud computing environments to support innovative research in educational measurement and assessment.
Primary Responsibilities
Technical Responsibilties:
Data Management and Analysis
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Collect, preprocess, and manage structured and unstructured data from diverse sources, ensuring data quality and integrity.
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Perform exploratory data analysis to identify trends, patterns, and actionable insights.
Model Development and Evaluation
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Design, implement, and validate predictive models and machine-learning algorithms using frameworks such as PyTorch/TensorFlow, and scikit-learn.
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Experiment with large language models and generative AI techniques (e.g., working with large language model APIs, prompt engineering) to support innovative research.
Deployment and Scalability
- Develop and maintain pipelines for model deployment in cloud computing environments (e.g., AWS, Azure) to ensure scalability and reproducibility.
Research and Collaboration
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Collaborate with scientists and cross-functional research teams to align data science efforts with program objectives
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Contribute to technical reports, presentations, and publications that disseminate research findings.
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Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
Requirements
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Proven research experience in education or closely related field (required)
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Demonstrable proficiency and experience in Python and/or R for data analysis and modeling.
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Hands-on experience with PyTorch/TensorFlow, Scikit-learn, and other machine learning frameworks.
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Familiarity with generative AI methods and their practical applications.
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Strong understanding of statistical methods, experimental design, and data visualization.
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Ability to work in cloud computing environments (e.g., AWS) for model deployment and data processing.
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Excellent problem-solving skills and adaptability to evolving research priorities.
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Effective written and verbal communication skills for collaborative research environments.
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Exceptional attention to detail, ensuring accuracy and reliability in data analysis, modeling, and reporting.
Education:
Master's degree in Data Science, Computer Science, Statistics, or a related quantitative field; or equivalent combination of education and experience.
ETS is mission driven and action oriented
- We are passionate about hiring innovative thinkers who believe in the promise of education and lifelong learning.