Data Scientist
USC Institute of Urology delivers comprehensive, multidisciplinary urologic care and advanced surgical services across a broad range of subspecialties. The Institute advances innovation by integrating clinical expertise with research, education, and new technologies to improve patient outcomes and care delivery. Through collaboration across USC and USC Health, the Institute supports translational work that brings novel approaches into practice. The USC Urology AI Center builds and deploys practical, reliable AI systems to support clinical operations and research within the Department of Urology. The Center focuses on applied AI engineering, including agentic, tool-using LLM workflows built on established technologies and integrated into real-world departmental processes.
USC Institute of Urology is seeking a Data Scientist.
In this role, the Data Scientist will support the design, development, testing, and deployment of agentic AI workflows within a healthcare environment. Based in the AI Center at the USC Institute of Urology, they will collaborate with a cross-disciplinary team of clinicians, researchers, and engineers to translate clinical and operational needs into practical, AI-driven solutions. Responsibilities include contributing to multi-step, API-driven workflows, integrating multi-modal data sources, and ensuring system reliability and traceability. The role focuses on building scalable, production-ready systems that enhance clinical operations, support research initiatives, and ultimately improve patient outcomes.
The successful candidate will be motivated, pro-active, resourceful, and detail-oriented. The position requires excellent organizational and communication skills with the ability to be decisive and adaptable. Candidates should have experience with agentic artificial workflows as well as a strong understanding of governance and security protocols for deploying AI solutions.
Essential job duties include, but are not limited to:
Build AI workflows that execute multi-step tasks through APIs and internal databases.
Integrate and normalize multiple data modalities to support workflow execution.
Implement RAG and grounding controls to support traceability and reduce unsupported outputs.
Design, troubleshoot and refine Agentic AI workflows and AI Agents to augment current healthcare applications.
Collaborate with clinicians, researchers, and operational stakeholders to translate needs into safe, testable, and measurable deliverables
Required Qualifications:
BS/MS in Computer Science, Engineering, or equivalent practical experience.
Strong Python, SQL programming skills, GitHub, and experience with ML frameworks (PyTorch, TensorFlow, etc).
Full stack software development, experience with JavaScript, Node.js, QT, or similar
Demonstrated experience building and deploying LLM applications beyond proto@types, including tool/function calling, workflow orchestration, structured outputs, and validation.
Experience implementing grounding/retrieval and reliability evaluation (test cases, regression checks, monitoring) and familiarity with security and privacy best practices for sensitive data.
Preferred Qualifications:
Experience integrating structured and unstructured data to support workflow automation and incorporating multimodal inputs where applicable.
Multi-step workflow design with escalation and human-in-the-loop safeguards.
Agentic AI workflow implementation and design of AI Agents (n8n, LangChain, LangGraph, AutoGen, CrewAI, or similar).
Cloud deployment, secure operations (AWS/Azure/GCP), APIs.
Multi-agent systems / planning / Reinforcement Learning fundamentals.
Lightweight fine-tuning or adaptation experience.
Follows established USC and department policies, procedures, objectives, performance improvement, attendance, safety, environmental, and infection control guidelines, including adherence to the workplace Code of Conduct and Compliance Plan.
This position is on-site and employee must report to work at the USC Health Science Campus in Los Angeles, CA when scheduled. Work hours and on-site days may be subject to change depending on business needs.
The annual budgeted range for this position is $120,213.99 - $155,525.71. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.
Minimum Education: Bachelor's degree Additional Education Requirements Combined experience/education as substitute for minimum education Minimum Experience: 2 years Minimum Skills: Experience using statistical computer languages (e.g., R, Python, SQL) to manipulate data and draw insights from large data sets. Experience working with and creating data models and data architecture, and using data visualization tools (e.g., Tableau, ArcGIS, D3.js). Knowledge of current data modeling tools and various machine-learning techniques and algorithms (e.g., clustering, decision-tree learning, artificial neural networks). Experience scripting and programming in several languages with common data science toolkits. Proficient use of query languages (e.g., SQL, MDX) and experience working with relational (e.g., MySQL, SQL Server, Oracle, Snowflake, Redshift) and non-relational (e.g., Mongo, NoSQL) databases. Knowledge of applied, statistical concepts and techniques skills (e.g., distributions, statistical testing, regression). Excellent written and oral communication skills. Ability to provide both detailed information and summaries to management-level individuals and groups. Experience developing customer relationships and delivering customer-focused service. Proven problem-solving and decision-making skills, and the ability to uncover root cause and evaluate different solution options. Preferred Education: Bachelor's degree Preferred Experience: 4 years Preferred Skills: Bachelor's degree in applied math, data science, computer science, statistics, or related field. Experience in data science, analytics, IT, cognitive engineering, or related fields. Demonstrated interest in data science and artificial intelligence, and experience in open domain (e.g. GitHub). Published writing on artificial intelligence and/or data science. Ability to write high-quality Python code. Familiarity with unit testing, source control and code review.
