Data Scientist Intern

The Data Scientist Intern supports the use of data analytics and machine learning to improve healthcare
outcomes and operational efficiency within a healthcare SaaS environment. Under the guidance of experienced
data scientists and cross-functional partners the intern will assist with analyzing datasets building models and
generating insights that inform product engineering and business decisions. The role provides hands-on
exposure to real-world healthcare data and applied data science practices.

Key Responsibilities:
1. Foundational Data Science & Analytics Skills
Assist with data exploration cleaning and preparation for analysis and modeling.
Support development and evaluation of basic statistical or machine learning models under supervision.
Apply foundational concepts in probability statistics and data analysis to assigned problems.
2. Data Engineering & Tooling Awareness
Support data workflows that may include structured and unstructured datasets.
Gain exposure to ETL concepts data pipelines and cloud-based data environments.
Assist with querying datasets using SQL and/or Python-based tools.
3. AI Readiness & Model Awareness
Develop familiarity with supervised and unsupervised learning concepts and how models are used in
production systems.
Support model validation basic experimentation or feature analysis as appropriate for intern-level
work.
Build awareness of ethical AI principles such as data privacy bias and responsible use.
4. Data Visualization & Communication
Help create basic visualizations summaries or dashboards to communicate findings.
Translate analytical results into clear insights for technical and non-technical stakeholders with
guidance.
Contribute to documentation of analyses assumptions and learnings.
5. Healthcare Domain & Compliance Awareness
Build foundational understanding of healthcare data concepts and workflows.
Follow team standards related to data privacy security and compliance (e.g. HIPAA awareness).
Learn how healthcare data standards (e.g. HL7 FHIR) influence analytics and modeling work
6. Collaboration & Learning
Collaborate with data scientists engineers and product partners as part of an agile team.
Participate in team meetings standups and reviews as a learning experience.
Demonstrate curiosity willingness to learn and openness to feedback

Required Qualifications:

Education & Experience
Currently pursuing a Bachelors or Masters degree in Data Science Computer Science Statistics
Mathematics or a related field. Graduating December 2026 or later.
Academic research or project experience involving data analysis statistics or machine learning
(coursework capstone or personal projects).
Interest in healthcare SaaS analytics or applied data science.

Other Preferred Knowledge Skills Abilities or Certifications:
Programming & Analysis Tools: Python and/or R; basic SQL knowledge.
Data & ML Libraries: Exposure to pandas NumPy scikit-learn TensorFlow or PyTorch (coursework
acceptable).
Visualization Tools: Familiarity with Tableau Power BI or Python visualization libraries (e.g. matplotlib
seaborn).
Cloud Exposure: Awareness of AWS Azure or GCP data services is a plus.
AI & Ethics Awareness: Interest in responsible AI data privacy and bias mitigation.
Communication: Ability to explain analytical findings clearly and concisely.