Data Science Intern | Fully Remote US

Summary

Hirevue is where hiring happens – transforming the way organizations discover, engage, and hire the best talent. As a Data Science Intern, you will support ongoing research initiatives and leverage machine learning to shape the future of hiring.

Responsibilities

• Support ongoing research initiatives that keep us on the cutting edge, including in agentic workflow development
• Work with machine learning models to build products and conduct research
• Write code to develop prototypes and utilities to extend or improve our product suite
• Drive the preparation of data used to train deep learning models and score unstructured data
• Assure quality of our software in terms of content, scoring, and functionality
• Performance modeling and data analysis

Skills

• Bachelor's degree required, with a Master's degree or PhD in progress in a quantitative/programming field (Computer Science, Statistics, Mathematics, Engineering, Psychology, Economics, Data Science, or related)
• Understanding of statistics, machine learning, and deep learning fundamentals
• Proficiency in Python, including common ML libraries (e.g., numpy, pandas, scikit-learn)
• Experience with version control (e.g., Git)
• Ability to analyze large datasets and draw meaningful, actionable insights
• Strong problem-solving skills — able to synthesize information from multiple sources to solve problems
• Team player with strong collaboration and communication skills; comfortable working closely with data scientists, engineers, and I/O Psychologists
• Self-motivated and able to work effectively with limited supervision; strong prioritization skills
• Awareness of state of the art methods in machine learning, deep learning, NLP, and/or generative AI
• Exposure to large language models (LLMs) and generative AI (e.g., prompt engineering, fine-tuning, agentic design patterns, agentic evaluation methods)
• Familiarity with SQL and database querying
• Familiarity with cloud platforms (AWS preferred) for ML workflows

Qualifications

Must Haves

• Bachelor's degree required, with a Master's degree or PhD in progress in a quantitative/programming field (Computer Science, Statistics, Mathematics, Engineering, Psychology, Economics, Data Science, or related)
• Understanding of statistics, machine learning, and deep learning fundamentals
• Proficiency in Python, including common ML libraries (e.g., numpy, pandas, scikit-learn)
• Experience with version control (e.g., Git)
• Ability to analyze large datasets and draw meaningful, actionable insights
• Strong problem-solving skills — able to synthesize information from multiple sources to solve problems
• Team player with strong collaboration and communication skills; comfortable working closely with data scientists, engineers, and I/O Psychologists
• Self-motivated and able to work effectively with limited supervision; strong prioritization skills

Nice to Haves

• Awareness of state of the art methods in machine learning, deep learning, NLP, and/or generative AI
• Exposure to large language models (LLMs) and generative AI (e.g., prompt engineering, fine-tuning, agentic design patterns, agentic evaluation methods)
• Familiarity with SQL and database querying
• Familiarity with cloud platforms (AWS preferred) for ML workflows