Intern - Data Scientist

Intern - Data Scientist

About nference

Our People

The Opportunity

What You'll Do

• Develop data pipelines to fetch, aggregate, clean, and preprocess raw patient data from electronic health records (EHRs).
• Apply statistical methods to understand data distributions, normalize variables, handle variations, detect anomalies, and assess data quality and integrity.
• Define, segment, and statistically validate data cohorts for analysis and research.
• Build basic batch-processing pipelines and automate data transformation workflows.
• Support LLM-assisted workflows using prompting, structured outputs, embeddings, and retrieval techniques for information extraction and cohort refinement.
• Conduct experiments, analyze results, and evaluate data and inference pipeline performance.
• Debug and optimize data processing and inference workflows.
• Use Git for version control and maintain reproducible data workflows.
• Document data cleaning rules, cohort definitions, analytical methods, and results to support reproducibility.
• Follow data privacy, security, and compliance requirements when handling healthcare data.

What We're Looking For

Required Qualifications

• Pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Economics, or a related quantitative field.
• Strong programming skills in Python, with practical knowledge of Pandas and NumPy for data manipulation and analysis.
• Solid understanding of statistical fundamentals, including data distributions, normalization, hypothesis testing, and anomaly detection.
• Strong analytical skills, with the ability to define, segment, and validate data cohorts using appropriate statistical methods.
• Understanding of machine learning and natural language processing (NLP) fundamentals.
• Familiarity with scikit-learn, SQL for data retrieval, and Git.
• Ability to work with messy, inconsistent, and unstructured datasets with strong attention to detail.
• Good problem-solving, documentation, and communication skills.
• Willingness to learn new tools and apply analytical techniques to real-world healthcare problems.

Preferred Qualifications

• Academic or personal projects involving data engineering, statistical data analysis, or cohort building.
• Exposure to LLM applications, retrieval-augmented generation (RAG), embeddings, or vector databases.
• Familiarity with LLM prompting and structured outputs for data extraction or analysis.
• Awareness of healthcare data privacy concepts and regulations, such as HIPAA.

What You'll Gain

• Hands-on Experience: Work with real-world healthcare data and practical data science workflows.
• Technical Learning: Gain exposure to machine learning, statistical analysis, data pipelines, and LLM applications.
• Mentorship: Learn from experienced data scientists and engineers.
• Meaningful Impact: Contribute to AI-powered solutions that support biomedical research and healthcare innovation.
• Career Development: Strengthen your analytical and technical skills in a collaborative, research-driven environment.

Equal Opportunity Employer