IT Data Scientist

Role Overview

You will work as an IT Data Scientist in a fully remote role, using advanced analytics and machine learning to improve large-scale operational and healthcare outcomes. The role involves building predictive models, extracting insights from structured and unstructured data, and supporting strategic decision-making.

Responsibilities

• Collaborate with stakeholders and subject matter experts to define and execute data-driven initiatives.
• Analyze large-scale structured and unstructured datasets with strong data quality/validation and interpretability.
• Develop and deploy statistical and machine learning models (e.g., regression, classification, clustering, forecasting, ensemble methods).
• Use NLP and LLM-based text analytics to extract insights from clinical notes, reports, and other unstructured sources.
• Perform exploratory data analysis and build scalable analytical workflows using Python, R, and SQL.
• Communicate results via reports, dashboards, visualizations, and presentations for both technical and non-technical audiences.
• Build reusable, well-documented code and analytical pipelines on cloud-based platforms.
• Apply collaborative software development best practices (e.g., Git, modular code standards).
• Manage multiple projects and balance iterative development with delivery timelines.

Requirements

• PhD in a relevant field (Data Science, CS, Statistics, Applied Mathematics, Engineering, Biomedical Informatics, etc.) or a Master’s degree with 2–4 years of relevant experience.
• Proven experience solving complex analytics and ML problems in real-world environments.
• Strong Python and/or R skills for advanced analytics/ML and advanced SQL.
• Expertise in statistical modeling, machine learning, AI, and predictive analytics.
• Experience with advanced techniques such as deep learning, Bayesian methods, NLP, LLMs, causal modeling, or knowledge engineering.
• Ability to work with large-scale heterogeneous datasets and translate data into actionable insights.
• Strong communication and storytelling skills.
• Familiarity with software engineering best practices and Docker/containerization.
• Must be authorized to work in the United States without current or future visa sponsorship.

Preferred

• Experience with healthcare datasets.
• MLOps principles, CI/CD pipelines, and production AI/ML deployment experience.