Intern, Data Science-Remote
Support Data Science team in clinical research. Develop ML models & analyze data.
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Overview
Support Data Science team in clinical research. Develop ML models & analyze data.
You have:
- Currently pursuing an MS or PhD degree in Computer Science, Biomedical Informatics, Engineering, Statistics, or a related quantitative field.
- Demonstrated experience with large-scale machine learning or foundation models, including training, fine-tuning, and evaluating LLMs (e.g., GPT, BERT) or vision models (e.g., CNNs, Vision Transformers).
- Strong programming skills in Python (or R), with experience in machine learning frameworks.
- In-depth knowledge of study design, data analysis, and statistical methodologies, with prior experience working with clinical or biomedical data (e.g., EHRs, images).
- Prior authorship or co-authorship of peer-reviewed publications is strongly preferred.
- Experience with interactive visualization tools (e.g., Plotly, Dash, D3.js, or React) is a plus.
- Excellent communication skills, with the ability to present results to both technical and non-technical audiences.
- Ability to deal professionally in a corporate or non-profit environment and assume responsibility for guiding projects and programs from inception through completion.
- Ability to work in a fast-paced, dynamic environment managing multiple priorities involving multiple entities.
- Intermediate to excellent proficiency in MS Word, Excel, Outlook and PowerPoint.
- Minimum availability of 20 hrs/wk, M-F between the hours of 8:00am-5:00pm.
- Required Equipment: Reliable WiFi Connection.
- Must be legally authorized to work in the United States for any employer without sponsorship, now or in the future.
Potential interview questions
| Describe your experience with machine learning models, particularly LLMs or vision models. | The interviewer wants to assess your technical knowledge and experience specific to the internship. | Share specific projects or experiences where you trained and evaluated models. |
| What programming languages are you most proficient in, and how have you applied them in data science projects? | This question gauges your technical skills in programming and their relevance to data science. | Pro members can see the explanation. |
| How do you approach data cleaning and processing? | Pro members can see the explanation. | Pro members can see the explanation. |
| Explain a project where you had to collaborate with cross-functional teams. What challenges did you face? | Pro members can see the explanation. | Pro members can see the explanation. |
| Can you provide an example of a statistical analysis you conducted and the results you derived? | Pro members can see the explanation. | Pro members can see the explanation. |
| What are your strategies for communicating technical results to a non-technical audience? | Pro members can see the explanation. | Pro members can see the explanation. |
| Share your experience with any data visualization tools you have used. | Pro members can see the explanation. | Pro members can see the explanation. |
| How do you prioritize tasks when working on multiple projects simultaneously? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 11 months ago
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Updated 10 months ago
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Source:
heart.org
