Data Scientist (ITS)
The Data Scientist at Confidential Client designs, develops, tests, and deploys agentic AI workflows to enhance clinical operations and research within a healthcare environment. Collaborating with clinicians, researchers, and engineers, the role focuses on building scalable, production-ready AI systems integrating multi-modal data and ensuring reliability, security, and traceability to improve patient outcomes. The position requires strong programming skills, experience with LLM applications, and adherence to governance and security protocols in AI deployment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Information Technology Services (Healthcare).
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
About the Role
Confidential Client’s Institute of Urology is hiring a Data Scientist to design, develop, test, and deploy agentic AI workflows that support clinical operations and research. This hands-on role sits within an AI Center focused on applied AI engineering for healthcare — building multi-step, API-driven LLM workflows, integrating multimodal data, and delivering production-ready systems with strong traceability, governance, and security.
Key Responsibilities
- Build and operate agentic AI workflows that execute multi-step tasks via APIs and internal systems.
- Integrate and normalize structured and unstructured data modalities to support workflow execution.
- Implement retrieval-augmented generation (RAG), grounding, and traceability controls to reduce unsupported outputs.
- Design, troubleshoot, and refine AI Agents and multi-step workflows with escalation and human-in-the-loop safeguards.
- Collaborate with clinicians, researchers, and operational stakeholders to translate needs into safe, testable deliverables.
- Develop validation, monitoring, regression checks, and reliability evaluation for deployed systems.
- Contribute clean, well-tested code and documentation; participate in design reviews and change control.
Minimum Qualifications
- BS or MS in Computer Science, Engineering, Data Science, or equivalent practical experience.
- 2+ years relevant experience (data science, ML engineering, or related); demonstrated ability to deliver production systems.
- Strong Python and SQL skills; proficiency with Git and software development best practices.
- Experience with ML frameworks such as PyTorch or TensorFlow.
- Hands-on experience building and deploying LLM applications beyond prototypes: tool/function calling, workflow orchestration, structured outputs, and validation.
- Experience implementing grounding/retrieval approaches, test-case based validation, monitoring, and familiarity with security/privacy for sensitive data (e.g., healthcare PHI).
- Full-stack development experience and familiarity with JavaScript/Node.js or similar.
Preferred Qualifications
- Experience integrating multimodal inputs (text, imaging, structured EHR data) into automated workflows.
- Prior work implementing agentic AI, multi-agent planning, or workflow automation tools (e.g., LangChain, LangGraph, AutoGen, n8n, CrewAI).
- Cloud deployment and secure operations experience (AWS, Azure, or GCP).
- Familiarity with monitoring, observability, and regression testing for AI services.
- Basic RL/planning fundamentals or lightweight fine-tuning/adaptation experience.
- Strong communication skills and proven ability to work in cross-disciplinary healthcare teams.
Location & Schedule
- This position is on-site. Employees must report to work at the client’s Health Science campus in Los Angeles, CA as scheduled.
- Work hours and on-site days may vary based on business needs.
Compensation
- Annual budgeted range: USD 120,213.99 – 155,525.71.
- When extending an offer, our client considers job scope, experience, education, internal equity, funding source, and applicable federal/state/local laws.
What We Value
- Safety-first design for clinical workflows and patient data protection.
- Clear documentation, reproducibility, and measurable validation.
- Pragmatic engineering that moves research into reliable production.
- Collaborative problem solving across clinical, research, and engineering teams.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
Negotiate a higher salary! Check the salary ranges for this job type in your area.
View My Salary Range