Data Science Intern - Garg Lab AI Program

Responsibilities

Selected Interns will utilize statistics and computer science to solve complex problems in healthcare. Problem areas include diagnostic analytics such as image analysis, signal processing and pattern recognition, NLP, scheduling, risk analysis and prevention, outcome analysis, targeting and socio-economic behaviors, personalization – including sentiment, interests and affinities modeling, and process improvement (e.g. making sure patients are referred to the care teams they need). The Intern will interact with vast amounts of clinical and non-clinical data (external data sources, digital, etc.). Interns will learn the data science lifecycle including data acquisition, transformation, data engineering, exploratory data analysis, feature engineering, algorithm development, and algorithm deployment into a relevant clinical and/or business context. Interns are expected to help formulate analytical questions, perform hypothesis testing, algorithm optimization, algorithm deployment, and integrate feedback rapidly from stakeholders. Candidate needs to have an open mind and ability to take concepts developed by other industries and apply them to healthcare. Candidates should be effective communicators and good team players. Candidates who have coursework, projects, and evidence of interest in data science (e.g., participating in Kaggle competitions) but lack industry experience are ideal for this position.

Qualifications


Current enrollment or recent graduate of undergrad or grad program in: Computer Science, Information Technology, Data Science, Physics, Statistics/Biostatistics, or other related field with strong quantitative analytical skills. School or project experience in applying data science approaches/tools. Proven written and oral communication skills are essential.AI experience/exposure or familiarity with AI principles is required. Courses and comfort level with at least one of the following: computer programming, machine learning, graph theory, algorithms, statistics, SQL, and linear algebra are essential for success. Experience with major programming languages is beneficial. Demonstrated initiative/innovation in coursework and projects.

Note: Preference will be given to candidates with experience applying AI and data science methods to healthcare quality improvement, clinical workflow optimization, operational efficiency, patient outcomes, or care delivery processes, as well as:
- Experience applying AI, machine learning, NLP, or predictive analytics to healthcare, research, or operational datasets.
- Familiarity with healthcare data sources, EHR systems, clinical coding, and quality improvement metrics.
- Proficiency in Python, R, SQL, or related analytical tools.
- Experience working with structured and unstructured data, including clinical text and operational data.
- Experience creating data visualizations, dashboards, and presenting analytical findings to diverse stakeholders.
- Demonstrated interest in healthcare innovation, gastroenterology, quality improvement, and clinical operations.

Mayo Clinic will not sponsor or transfer a visa for this position, which includes F1 OPT STEM.


Site Description


Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. 


Equal Opportunity


All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law".  Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.