Entry Level Data Scientist (Remote)

Join Our Data Science Team as an Entry Level Data Scientist

City of Hope is seeking a motivated Entry Level Data Scientist to join our growing analytics team in a fully remote capacity. In this role, you will collaborate with cross‑functional stakeholders to transform complex healthcare data into actionable insights that drive improved patient outcomes and operational efficiency.

What You’ll Do

• Clean, preprocess, and analyze large structured and unstructured datasets using Python (pandas, NumPy) and SQL.
• Build and evaluate predictive models (regression, classification, clustering) with scikit‑learn, XGBoost, or LightGBM.
• Develop reproducible data pipelines and visualizations (Matplotlib, Seaborn, Plotly) for both technical and non‑technical audiences.
• Participate in the full model lifecycle: from problem framing and feature engineering to deployment monitoring and model retraining.
• Document methodologies, experiments, and findings in clear technical reports and Jupyter notebooks.

Why You’ll Love It Here

• Fully remote work environment with flexible hours.
• Access to a rich, real‑world healthcare data lake spanning clinical, genomic, and operational domains.
• Mentorship from senior data scientists and opportunities to publish internal white papers.
• Competitive salary ($70,000–$75,000 annually) plus comprehensive benefits including health, dental, vision, 401(k) match, and tuition reimbursement.

We value diversity of thought and background. If you are passionate about using data science to make a tangible impact in healthcare, we encourage you to apply.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field (graduating 2024‑2026).
• Proficiency in Python (pandas, NumPy, scikit‑learn) and SQL.
• Solid understanding of statistical concepts (hypothesis testing, regression, probability distributions).
• Experience with version control (Git) and reproducible research practices (Jupyter, virtual environments).
• Strong communication skills with the ability to translate technical findings for diverse audiences.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker) is a plus.
• Prior internship, research project, or coursework involving end‑to‑end machine learning projects preferred.