Internship: Data Scientist, Health Informatics at Quest Diagnostics

Feedinkoo; United States; Remote; USD 20,664 - 34,440; Part time

Job summary

Feedinkoo is seeking a Paid Intern: Data Scientist in Health Informatics. This role allows for remote work, offering a flexible schedule averaging 20 hours a week. The candidate will work with a cross-functional team to develop informatics solutions using healthcare data.

Qualified candidates are Master’s degree students in quantitative fields such as Data Science and must possess strong Python and SQL skills. The position includes responsibilities in data engineering, analytics, and presentations.

Qualifications

• Master’s degree student in Data Science, Biostatistics, Bioinformatics, Public Health, or similar.
• Ability to work on large data sets using Python.
• Candidates with advanced Python and SQL skills are strongly preferred.

Responsibilities

• Develop and deliver informatics and analytics services using varied healthcare-related data.
• Utilize data mining and predictive analytics to identify patterns in diagnostic test results.
• Contribute to product development for public health entities.

Skills

Data Science programming

Python

SQL

Data mining

Machine learning

Deep learning

Data visualization

Education

Master’s degree in a quantitative field

Tools

Tableau

AWS-Quicksight

Power-BI

SAS-VIYA

AWS-Sagemaker

Job description

Paid Intern: Data Scientist, Health Informatics

This person can work 100% remotely with a flexible schedule totaling, on average, 20 hours a week, depending on business needs. Candidate must be located in the US.

Responsibilities

• Work remotely with a cross‑functional team of analysts, medical doctors, business leaders, and IT professionals to develop and deliver informatics and analytics services and solutions utilizing data from varied healthcare related data sources.
• Utilize strong data science programming, quantitative and analytical skills to standardize, integrate, analyze, and model large clinical data.
• Identify meaningful patterns in diagnostic test results using data mining, pattern recognition techniques (clustering, association rule mining, and decision trees), and predictive analytics (regression modelling, machine and deep learning, neural networks).
• Contribute to product development including visualizations and statistics‑based altering systems to enable public health entities and clinicians to better serve their communities.
• Build scaled data engineering algorithms to minimize the need for additional data curation.
• Work on end‑to‑end projects from data engineering, through advanced analytics, to final presentation and visualization.
• Other duties as assigned.

Qualifications

• Master’s degree student in a quantitative field including Data Science, Biostatistics, Bioinformatics, Public Health, Computer Science, Economics, Statistics, or Mathematics.
• Strong ability to work on multiple projects simultaneously, balancing priorities, and to work on cross‑functional teams.
• Ability to work on large data sets using Python is required.
• Candidates with both advanced Python and SQL skills are strongly preferred.
• Experience using data mining, pattern recognition, machine learning, deep learning, statistical and/or mathematical programming and modeling preferred.
• Experience with visualization tools like Tableau, AWS‑Quicksight, Qlik, Power‑BI, SAS‑VIYA preferred.
• Use of other tools like AWS‑Sagemaker preferred.
• Professional data science/data engineering experience preferred.
• Experience with clinical/health care data and specifically lab data preferred.
• Excellent communication skills strongly preferred.
• Experience with Microsoft Office products required; expertise in Excel preferred.

Open to limited travel.

All requirements are subject to possible modifications to reasonably accommodate individuals with disabilities.

Equal Opportunity Employer: Women / Minorities / Veterans / Disabled / Sexual Orientation / Gender Identity. Equal Opportunity Employer: Race/Color/Sex/Sexual Orientation/Gender Identity/Religion/National Origin/Disability/Vets or any other legally protected status.