Research Data Analyst Radiology Bharti's Lab

As a Research Data Analyst, you will play a hands-on technical role with increasing intellectual ownership in building, querying, and analyzing large-scale clinical datasets using Snowflake, SQL, and Python, supporting the development, evaluation, and deployment of machine learning models for conference submissions and peer-reviewed manuscripts within one of the nation's largest healthcare environments. You will work closely with clinicians, data scientists, PhD students, and engineers to translate complex clinical questions into scalable computational pipelines and research outputs.

This position offers opportunities to contribute intellectually to study design, methodological development, and scientific writing, with mentorship tailored to candidates planning to pursue PhD or MD-PhD training in computer science, machine learning, biomedical informatics, or related fields. Research Data Analysts at TIRIC gain direct exposure to real-world clinical data at scale, rigorous applied machine learning research, and collaborative academic environments that support long-term research and academic career development.

This role is ideal for a self-driven, technically strong candidate seeking deep exposure to applied machine learning, healthcare data infrastructure, and translational research, without significant direct patient interaction. TIRIC is deeply committed to mentorship and career development, and this role is designed to prepare trainees for careers in academia, biomedical AI, public health, or biomedical research.

Responsibilities:

Responsibilities include, but are not limited to, the following:

Data Engineering & Analytics

• Querying and managing large-scale clinical datasets using Snowflake and SQL
• Building reproducible data pipelines using Python and related tools (e.g., Pandas, NumPy)
• Performing data cleaning, validation, quality control, and documentation
• Organizing multimodal datasets (EMR, imaging-derived variables, clinical outcomes)

Machine Learning & Modeling

• Supporting and leading development, refinement, and evaluation of machine learning models
• Debugging and optimizing analytical workflows in collaboration with MIT data scientists
• Conducting exploratory data analysis and feature engineering

Research & Reporting

• Analyzing quantitative and qualitative data
• Generating figures, tables, and summary reports for internal reviews and publications
• Presenting findings at weekly lab meetings and multidisciplinary forums

Clinical & Translational Research Support

• Performing structured electronic medical record (EMR) reviews
• Assisting with coordination of multi-center clinical studies and trials
• Contributing to protocol development, SOPs, and manuals of operations (MOOPs)

Scholarly Writing & Regulatory Work

• Assisting in preparation of manuscripts, abstracts, grant proposals, and presentations
• Conducting literature reviews and synthesizing findings
• Preparing and submitting materials for the Institutional Review Board (IRB), including amendments and annual reports

Collaboration & Operations

• Organizing and participating in interdisciplinary meetings with MGB and MIT collaborators
• Collecting user and clinician feedback via interviews and focus groups
• Supporting project management tasks such as agendas, documentation, and meeting minutes

Qualifications

Required

• Bachelor's degree in Computer Science, Data Science, Engineering, Applied Mathematics, or a related field
• Strong working knowledge of SQL and experience querying large relational databases
• Proficiency in Python for data analysis and machine learning workflows (e.g., PyTorch, Pandas, NumPy)
• Comfort working with complex, real-world datasets

Preferred

• Prior experience querying and managing data in Snowflake or comparable cloud-native, distributed analytics platforms
• Experience with healthcare, EMR, or large administrative datasets
• Exposure to machine learning, statistics, or computational research
• Coursework in artificial intelligence, machine learning, deep learning, and/or data science
• Familiarity with version control (e.g., Git) and reproducible research practices

Personal Attributes

• Highly motivated, independent, and detail-oriented
• Strong problem-solving and analytical skills
• Comfortable working in interdisciplinary teams with clinicians, engineers, and researchers
• Excellent written and verbal communication skills
• Interest in healthcare, medicine, public health, or medical AI

Work Environment & Mentorship

TIRIC is an inclusive, collaborative, and intellectually rigorous research environment. Research Assistants receive close mentorship, meaningful technical ownership, and opportunities for co-authorship on publications and grants. Our former Research Assistants, Data Analysts and trainees have gone on to top medical schools, PhD programs, industry research roles, and public health careers.

TIRIC embraces diversity and is committed to building an equal-opportunity team representing a wide range of backgrounds, perspectives, and skills.

Start date: Spring/Summer 2026 (flexible)