• Leverage data to solve a wide variety of meaningful, business problems. • Partner closely with Engineering, PM, and Care Operations to define strategy. • Design and implement frameworks to measure data product effectiveness. • Research operational problems and identify solutions. • Lead design, implementation, and evaluation of models. • Champion usage of LLM-driven workflows across the company.

Role Description Data Scientists at Mayo Clinic perform detailed analysis of large bodies of heterogeneous data in order to discover new patterns and insights having an impact upon patient health and augmenting human capabilities. Candidate has deep expertise in AI, machine learning, deep learning, statistical data processing, regression techniques, neural networks, decision trees, clustering, pattern recognition, probability theory and data science methods and the mathematical theories underlying these tools used to analyze data. Has deep knowledge of healthcare data types, topics, and scientific challenges and approaches. Work with knowledge architects, informaticians and clinicians at Mayo, and partner outside companies to develop and deploy applications to bring AI and analytic solutions to nontechnical users, often at the point of care. Designs and develops scripts or software applications to support data management, data extraction, data analysis, and AI as required. This position may develop predictive and prescriptive models to address complex problems, discover insights, and identify opportunities using machine learning, statistical techniques, and data mining. Provides Consultative Services at an enterprise level to departments/divisions and/or may lead scientific projects. May have direct and indirect reports. - Provides deep data insights for complex business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data. - Develops predictive and prescriptive models to address complex problems, discover insights, and identify opportunities using machine learning, statistical techniques, and data mining. - Makes presentations on assigned projects or proposals. - Conducts advanced data analysis and designs highly complex algorithm systems. - Functions independently and initiates judgment in handling delegated responsibilities. - Experience leading technical/quantitative teams. - Develops experimental design approaches to validate findings or test hypotheses. - Identifies/creates the appropriate algorithm to discover patterns. - Leads and directs the interpretation of data analysis and writing reports. 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. Company Description Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic. Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.

• Design, develop, and assess AI models focused on detecting P2P scams, with a particular emphasis on document verification and payment proof tampering. • Research and prototype large language model (LLM)-based solutions to enhance automated detection, generate interpretable rule-based explanations, and support scam pattern discovery. • Investigate and implement cutting-edge image embedding techniques to extract meaningful features for downstream applications such as clustering and classification. • Collaborate closely with data scientists and engineers to optimize the detection pipeline and deliver actionable insights to key stakeholders.

• Analyze large-scale healthcare datasets (medical & pharmacy claims, EHR, labs, SDOH) • Design and execute real-world evidence (RWE) studies • Apply statistical and quasi-experimental methods to evaluate intervention impact • Develop predictive and analytical models to support population health strategies • Analyze patient journeys, care patterns, and provider networks • Identify healthcare disparities and access barriers • Translate analyses into actionable insights for stakeholders