Sr. Data Scientist

Sr. Data Scientist

Annual Compensation: $170,000 - $175,000

Location: Remote; Dallas, TX preferred

Why Choose GMR? Global Medical Response (GMR) and its family of solutions are dedicated to delivering compassionate, quality medical care, primarily in the areas of emergency and patient relocation services. Here you'll embark on meaningful work that will make an impact on you and the customers we serve. View the stories on how our employees provide care to the world at www.AtaMomentsNotice.com.

GMR's Core Behaviors-keep care at the center, raise your hand, seek to understand, find a way together and be accountable-unite our teams and set us apart in emergency medical services.

We are looking for an exceptional Senior Data Scientist to join our growing team and help shape the future of data-driven innovation in EMS healthcare. This role blends technical expertise with curiosity, creativity, and a passion for delivering impactful insights. You will play a key role in building our Data Science function and driving advanced AI/ML solutions from concept to deployment.

* AI and Machine Learning: Design, build, and deploy predictive, generative, and agentic AI models for healthcare applications.

* Data Analysis & Insights: Perform advanced analytics and exploratory data analysis (EDA) on structured and unstructured healthcare datasets, including EHR, claims, and demographic data, ensuring HIPAA compliance.

* Collaboration: Work closely with IT and business teams to identify use cases, define requirements, and deliver impactful solutions.

* Innovation Leadership: Lead machine learning projects across healthcare, GIS, and logistics domains; champion new methodologies and best practices.

* Data Science Subject Matter Expertise: As a senior Data Scientist, lead and drive methodologies and approaches to solving complex problems

* End-to-End Delivery (Full stack): Manage full lifecycle of AI solutions-from prototyping to production deployment and system integration.

* Model Monitoring: Deploy, monitor, and optimize traditional ML, Generative AI, and Agentic models for continuous improvement.

* Stakeholder Engagement: Partner with business leaders to translate complex data into actionable insights and recommendations.

* Education: Master's or Ph.D. in Data Science, Computer Science, Statistics, or related field.

* Experience: 6-8 years of hands-on experience in applied machine learning, predictive modeling, and generative AI, preferably working with clinical (structured & unstructured), Geographic Information System (GIS) datasets.

* Strong Proficiency in Python, R, and Java; strong SQL skills.

* Expertise in ML frameworks (TensorFlow, PyTorch) and data manipulation libraries (pandas, dplyr).

* Experience with data visualization tools (e.g. Streamlit/Dash, matplotlib, ggplot2, Plotly).

* Familiarity with Generative AI techniques, RAG pipelines, and agentic frameworks like LangChain or LlamaIndex.

* Knowledge of cloud-based AI/ML platforms (Azure, Databricks or equivalent).

* Strong foundation in statistical modeling, hypothesis testing, regression analysis, time-series forecasting, and Bayesian methods.

* Experience with supervised and unsupervised learning, ensemble methods, deep learning architectures, process mining and NLP techniques.

* Understanding of model evaluation metrics, bias/variance trade-offs, and techniques for interpretability and fairness.

* Excellent communication and ability to simplify complex concepts for diverse stakeholders. Strong multitasking and project management skills.

* Collaborative & Innovative: Work in a team that values creativity, learning, and impact.

* Mission-Driven: Help us achieve our goal of driving 90% of EMS requests through digital platforms and delivering new services to customers.

Global Medical Response and its family of companies are an Equal Opportunity Employer, which includes supporting veterans and providing reasonable accommodations for individuals with a disability.

Check out our careers site benefits page to learn more about our benefit options.