Senior Data Science Analyst - DLMP
About The Position
Mayo Clinic is a top-ranked healthcare provider dedicated to patient needs and employee well-being, offering competitive compensation, comprehensive benefits, and opportunities for continuing education and career advancement. This role involves performing detailed analysis of large, heterogeneous datasets to discover patterns and insights impacting patient health and augmenting human capabilities. The candidate will leverage advanced expertise in AI, machine learning, deep learning, statistical data processing, and various mathematical theories to analyze data. Advanced knowledge of healthcare data types, topics, and scientific challenges is also required. The role may involve collaboration with internal knowledge architects, informaticians, and clinicians, as well as external partners, to develop and deploy AI and analytic solutions for non-technical users, often at the point of care. Responsibilities include applying and modifying scripts/software for data management, extraction, analysis, and AI, as well as developing predictive models using advanced statistical modeling, operations research, machine learning, or data mining techniques. Consultative services at an enterprise level and support for scientific projects under senior supervision are also part of the role. The position requires a two-year commitment and is not eligible for visa sponsorship or F-1 STEM OPT extension.
Requirements
- A master’s degree in engineering, computer science, mathematics, health science, or a related field with 4 years of experience, or a bachelor’s degree with 6 years of experience.
- Extensive experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries, showcasing an understanding of healthcare technology.
- Demonstrated leadership in managing complex projects, with a proven ability to navigate intricate project requirements and deliver successful outcomes.
- Proficiency in fostering collaboration across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.
- Demonstrated expertise in cloud infrastructure environment and software development tools.
- Experience working with large, complex, and heterogeneous data sets, preferably in healthcare.
- Skilled in AI/ML techniques and frameworks.
- Familiarity with best practices in data engineering, data science, AI Engineering, and the MLOps communities.
- Demonstrated initiative in administration, education, software development, and technical reporting.
- A commitment to mentoring and training less-experienced team members, coupled with strong interpersonal, communication, and time management skills.
Nice To Haves
- Experience developing, validating, or deploying AI/ML models in healthcare, pathology, laboratory medicine, or clinical operations.
- Familiarity with multimodal clinical data, digital pathology images, whole-slide imaging, image analysis, including integration of imaging, laboratory, pathology, molecular, structured EHR, and unstructured clinical data.
- Experience with MLOps, model lifecycle management, model monitoring, version control, reproducible pipelines, or scalable deployment workflows.
- Experience translating AI/ML models from proof-of-concept into operational, production-ready, or clinically deployable solutions.
- Working knowledge of cloud-based or enterprise-scale data science environments, high-performance computing, or secure healthcare data platforms.
- Proficiency with Python, R, SQL, machine learning frameworks, statistical modeling tools, and data visualization methods.
- Strong ability to communicate complex technical concepts to nontechnical clinical, operational, and executive audiences.
Responsibilities
- Provides advanced data insights for complex business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data.
- Has advanced expertise in the methods used to analyze data and advanced knowledge of data types, topics, and scientific challenges and approaches.
- Will work with other staff in developing data analysis tools and predictive models, using advanced data analysis techniques and artificial intelligence and machine learning.
- Participates in discovery processes with stakeholders to identify the business requirements and the expected outcome.
- Leads the interpretation of data analysis and writing reports.
- Advance AI and machine learning solutions specifically for digital pathology and multimodal clinical data.
- Work as part of an AI Operations team focused on moving AI models into clinically deployable products in collaboration with clinical, technical, enterprise informatics, IT, and regulatory teams.
- Support the full AI product development lifecycle by establishing best practices for model evaluation, quality assurance, reproducibility, and regulatory documentation.
- Collaborate directly with pathologists, laboratory physicians, clinicians, computational scientists, enterprise informatics, IT, regulatory teams, and software engineering teams.
- Develop AI solutions that address real-world clinical needs, not only general business or scientific problems.
- Emphasize clinical translation of AI/ML solutions, moving beyond data analysis and predictive modeling into operational clinical use.
Benefits
- Medical: Multiple plan options.
- Dental: Delta Dental or reimbursement account for flexible coverage.
- Vision: Affordable plan with national network.
- Pre-Tax Savings: HSA and FSAs for eligible expenses.
- Retirement: Competitive retirement package to secure your future.
- Continuing education and advancement opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
