Data Scientist

About the role

Data Scientist

📍 Location: Texas, United States (Remote)

🏢 Industry: Hospitals and Health Care

💼 Work Setting: Remote (Continental U.S.) with occasional travel.

Are you passionate about transforming complex data into meaningful insights that drive innovation and better outcomes? We are looking for a Data Scientist to leverage advanced analytics, machine learning, and AI-driven solutions to solve real-world challenges and support data-informed decision-making.

Key Responsibilities

Analyze, validate, and interpret large and complex datasets to uncover actionable insights.

Design, build, test, and deploy machine learning models to address business and research needs.

Develop and optimize Generative AI and Large Language Model (LLM) solutions using effective prompt engineering techniques.

Apply statistical methodologies to evaluate data, identify trends, and provide recommendations.

Create impactful dashboards, reports, and visualizations for both technical and non-technical stakeholders.

Collaborate with cross-functional teams, including product, engineering, research, and business stakeholders, to solve complex analytical problems.

Develop scalable, production-ready code and contribute to multiple analytics initiatives within a dynamic environment.

Required Qualifications

Master's degree with at least 2 years of relevant experience, Bachelor's degree with at least 4 years of relevant experience, or equivalent practical experience.

Proven experience in Data Science, Machine Learning, Analytics, Statistics, or a related quantitative field.

Strong programming skills in Python or R, along with expertise in SQL and database querying.

Hands-on experience applying statistical techniques to generate insights and support decision-making.

Experience creating data visualizations, dashboards, analytical reports, and supporting machine learning solutions.

Preferred Qualifications

Advanced degree (Master's or PhD) in Data Science, Statistics, Computer Science, Bioinformatics, or a related discipline.

Experience developing machine learning models using techniques such as Natural Language Processing (NLP), Deep Learning, Random Forests, and Gradient Boosting.

Practical experience with Generative AI, LLMs, and prompt engineering.

Exposure to cloud-based analytics platforms and modern data processing environments.

Familiarity with software development and deployment tools such as Git, Docker, Airflow, and MLOps frameworks.

Experience working with healthcare, life sciences, clinical, genomic, or other regulated datasets is a plus.

Understanding of data privacy, compliance, and industry-specific data standards.

Work Arrangement

Remote work opportunity with flexibility to collaborate across distributed teams.

Occasional travel may be required based on business needs.