Associate R & D Data Scientist

Educational Testing Service • Indianapolis, IN • 1d ago

About ETS:

ETS is a global education and talent solutions organization enabling lifelong learners worldwide to be future-ready. For more than 75 years, we've been advancing the science of measurement to build benchmarks for fair and valid skill assessment across cultures and borders. Our worldwide impact extends through our renowned assessments including TOEFL®, TOEIC®, GRE® and Praxis® tests, serving millions of learners in more than 200 countries and territories. Through strategic acquisitions, we've expanded our global capabilities: PSI strengthens our workforce assessment solutions, while Edusoft, Kira Talent, Pipplet, Vericant, and Wheebox enhance our educational technology and assessment platforms across critical markets worldwide.

Through ETS Research Institute and ETS Solutions, we're partnering with educational institutions, governments, and organizations globally to promote skill proficiency, empower upward mobility, and unlock opportunities for everyone, everywhere. With offices and partners across Asia, Europe, the Middle East, Africa, and the Americas, we deliver nearly 50 million tests annually. Join us in our journey of measuring progress to power human progress worldwide.

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

Collect, preprocess, and manage structured and unstructured data from diverse sources, ensuring data quality and integrity.

Perform exploratory data analysis to identify trends, patterns, and actionable insights.

Model Development and Evaluation

Design, implement, and validate predictive models and machine-learning algorithms using frameworks such as PyTorch/TensorFlow, and scikit-learn.

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

Collaborate with scientists and cross-functional research teams to align data science efforts with program objectives

Contribute to technical reports, presentations, and publications that disseminate research findings.

Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

LI-MM1

Remote

Demonstrable proficiency and experience in Python and/or R for data analysis and modeling.

Hands-on experience with PyTorch/TensorFlow, Scikit-learn, and other machine learning frameworks.

Familiarity with generative AI methods and their practical applications.

Strong understanding of statistical methods, experimental design, and data visualization.

Ability to work in cloud computing environments (e.g., AWS) for model deployment and data processing.

Excellent problem-solving skills and adaptability to evolving research priorities.

Effective written and verbal communication skills for collaborative research environments.

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

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