Senior Data Scientist & AI Engineer - Medicine - 140339

The Department of Medicine is the largest department within the UC San Diego School of Medicine, supporting the institution's academic, clinical, educational, and research missions. It encompasses 23 actively managed financial units spanning central administration, a medical residency program, self-supported operating activities, and medical specialties. The Department of Medicine Business Office provides comprehensive financial, operational, and data-driven support for this large and complex enterprise. The team includes financial analysts and accountants, financial support personnel, and data science professionals. Together, they oversee more than $200M in annual financial activity across the Department's non-research activities, the entire Medicine internal control portfolio, and medical personnel operational performance.

Reporting to the Senior Director of Business Intelligence, this position serves as a skilled data science, artificial intelligence, machine learning, and database and cloud infrastructure professional responsible for transforming complex financial and operational datasets into actionable insights that drive organizational performance and decision-making. The role requires resolving highly complex problems through advanced modeling, algorithm development, and in-depth analysis of variable data factors, and developing innovative, data-driven solutions that support operational efficiencies, financial accuracy, and strategic planning. This position will design, develop, deploy, and provide for ongoing administration of machine learning systems and large language model infrastructure; engineer and maintain SQL Server and cloud-based database environments; and develop automated algorithms and AI-driven analytical workflows to support financial integrity, data quality assurance, and plain-language analysis of departmental financial and operational data for technical and non-technical stakeholders. Applies skills and experience as an independent contributor and collaborative team partner to projects of medium size at all levels of complexity, or to portions of large, multidimensional projects.

• Seven years of related experience, education/training, OR a Bachelor's degree in related area (data or computer science, statistics, business analytics, accounting, finance) plus three years of related experience/training.

• Thorough knowledge of business intelligence functions, analytics, industry standards and best practices. Includes in-depth knowledge of machine learning methodologies, large language model (LLM) architecture, and AI-driven analytical system development, encompassing model training and validation, performance evaluation, bias detection, and iterative improvement practices as applied to financial and operational information.

• Thorough knowledge of relevant internal databases, BI applications and tools. Ability to produce high-quality reports and documentation. Includes advanced skill in SQL Server database administration, query optimization, data import/export pipeline design, and cloud-based data platform management. Demonstrated ability to design, maintain, and optimize scalable data environments that support BI and AI workloads. Skilled in the use of spreadsheet and database software, such as advanced functionality in Microsoft Excel, including the utilization of PowerQuery and external data connections.

• Strong critical thinking and problem-solving skills to manage complex information, assess problems, and develop and effective solutions. Includes the demonstrated ability to independently manage, with limited direction and oversight, complex and multidimensional data science projects, applying advanced critical thinking to the development and validation of machine learning models, automated auditing algorithms, and AI-generated analytical outputs, with particular attention to successful attainment of department goals.

• Detail oriented, with ability to manage time and organize competing priorities. Includes the ability to independently manage the full lifecycle of business intelligence, data science, and AI projects while balancing multiple concurrent analytical responsibilities in an environment of dynamic priorities.

• Strong written and verbal communication skills with the ability to convey complex information in a clear, concise manner. Includes the ability to translate highly technical AI, machine learning, and data science concepts and analytical results into plain-language summaries, reports, and presentations, for non-technical stakeholders.

• Strong interpersonal skills for effective collaboration with a broad range of professional and technical staff. Includes the ability to act as a positive and contributing team member with a strong professional commitment to cultivating collaborative relationships with personnel of diverse backgrounds, levels, and responsibilities, and to providing staff mentorship that sustains a climate of trust and shared purpose.

• Proven ability to serve as a technical resource providing advice and counsel on business intelligence issues. Includes the ability to provide technical leadership on data and AI infrastructure, machine learning model selection and evaluation, LLM development and deployment, and data governance practices.

• Advanced proficiency in Python and SQL for data engineering, statistical modeling, machine learning development, and automated workflow construction, including advanced skill in SQL Server administration, query optimization, index management, and data pipeline design and maintenance.

• Demonstrated ability to write, test, and maintain production-quality code supporting BI, AI, and data science operations with appropriate version control. Experience with programming languages and tools such as Python, T-SQL, R, M-Code, Visual Basic for Applications, C++ / C#, Tableau, and SSMS, with a demonstrated aptitude and commitment to rapidly learning new technologies as needed to support business intelligence and analytical tasks and automation.

• Master's degree in data science or a related area and/or equivalent experience/training.

• Knowledge of financial accounting principles, practices, systems, reporting techniques, and analysis of operational performance metrics.

• Knowledge of data governance, privacy regulations, and institutional compliance requirements as they apply to the design and deployment of data servers, AI/LLM systems, and automated analytical workflows.

• Employment is subject to a criminal background check.

• Occasional evenings and weekends may be required.

• Must be able to work various hours and locations based on business needs.