Chief Data Scientist; HCA​/ITD

• Every New Mexican has access to affordable health care coverage through a coordinated and seamless health care system.

• We ensure that New Mexicans attain their highest level of health by providing whole-person, cost-effective, accessible, and high-quality health care and safety-net services.

• Leverage purchasing power and partnerships to create innovative policies and models of comprehensive health care coverage that improve the health and well-being of New Mexicans and the workforce.
• Achieve health equity by addressing poverty, discrimination, and lack of resources, building a New Mexico where everyone thrives.
• Implement innovative technology and data-driven decision-making to provide unparalleled, convenient access to services and information.
• Build the best team in state government by supporting employees' continuous growth and wellness.

The Manager, Data Science / Chief Data Scientist will:

• Ensure that HCA remains at the forefront of innovative analytic solutions and algorithms that support informed decision-making;
• Play a key part in advancing HCA into the fields of prescriptive and cognitive analytics;
• Enhance data literacy across all levels of HCA;
• Equip the organization with additional tools that support HCA's goal of implementing innovative technology to provide unparalleled and convenient access to services and information.

The Manager, Data Science / Chief Data Scientist is responsible for:

• Serving as the department's lead expert and sharing best practices in statistics, data modeling, applied mathematics, quantitative research, and predictive modeling;
• Developing relationships with cross departmental partners to build collaborative analytic efforts that drive policy, reduce inequality, and promote equity across programs serving New Mexicans;
• Translating business needs into analytics and reporting requirements that support executive decision-making and workflow improvements;
• Encouraging informed risk-taking and acting as a catalyst for innovation by generating practical, sustainable, and creative options that solve problems and create departmental opportunities while maximizing existing resources;
• Performing large-scale experimentation and building data driven models to answer key business questions;
• Proactively mining and analyzing large structured and unstructured datasets, performing experimentation, identifying trends and hidden patterns, defining and monitoring metrics, creating data narratives, and building tools that drive decision making;
• Researching and implementing cutting-edge techniques in machine learning, deep learning, and artificial intelligence to increase analytic efficiency;
• Providing technical support for internal studies, including evaluation of outcomes, processes, program implementation, needs assessments, performance measurement, feasibility analyses, ex post/ex ante studies, and program monitoring;
• Proactively developing, maintaining, and promoting technical expertise in machine learning, generative AI, and adjacent technologies, while remaining up to date on emerging trends and best practices;
• Ensuring effective design and quality deliverables in the machine learning space by designing and developing ML and deep learning systems, running tests and experiments, and implementing appropriate algorithms;
• Applying statistical analysis and visualization techniques to diverse data using methods such as hierarchical clustering, t-SNE, and PCA;
• Developing a training program focused on basic statistics and data analysis tools for new analysts and interested staff, supporting the department's transition toward data driven decision making.

The Chief Data Scientist must understand the HCA strategy to develop innovative analytical solutions that advance HCA's mission and goals, ensuring that analytics efforts support the organization's overall direction.

• Staying aligned with the HCA Strategy Team, including;
• HCA Secretary;
• Deputy Secretaries;
• Directors, and;
• CIO.

The Ideal Candidate will have:

Education:

• PhD or MSc in Statistics, Data Science, Mathematics, Physics, Economics, Engineering, Public Health, Epidemiology, or a related quantitative research field;
• Specialization in advanced statistical methodologies, machine learning, or artificial intelligence is preferred.

Experience:

• Ten (10) years of relevant project experience in launching, planning, and executing data science projects, including statistical analysis,…