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About
We are seeking a Senior Data Scientist with deep expertise in production-level AI systems, specifically Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs). This role will lead the design, development, and deployment of advanced data science and AI solutions that directly impact business performance, clinical workflows, and decision-making. This is a highly cross-functional role requiring strong technical depth, business acumen, and the ability to operate in regulated environments. Key Responsibilities
Lead the design, development, and deployment of data science and AI/ML solutions, including LLM-powered systems Build and operate production-grade RAG systems, focusing on retrieval quality, orchestration, cost optimization, and observability Develop and implement predictive models and advanced analytics to drive business outcomes (customer experience, revenue, operational efficiency) Mine and analyze large datasets to support product development, clinical insights, and business strategy Develop custom data models, algorithms, and machine learning solutions Evaluate and improve data sources, pipelines, and data quality Collaborate with cross-functional teams (Clinical SMEs, Quality, IT/Security, Product, and Executive stakeholders) to translate business needs into technical solutions Monitor and optimize model performance, ensuring scalability, accuracy, and compliance Support and enhance data infrastructure, including cloud-based environments (AWS/Azure) Ensure data security and compliance, particularly in regulated or post-market environments Contribute to intellectual property and innovation initiatives Mentor junior team members and lead cross-functional projects Specialized Requirements
Hands-on experience building and operating production RAG and LLM systems (not just experimentation or notebook work) Strong understanding of: retrieval quality and evaluation, system orchestration and architecture, cost optimization strategies, observability and monitoring of AI systems Experience with evaluation frameworks in complex, high-cardinality classification problems, especially where: labels overlap, outputs feed into regulated or clinical workflows Emphasis is on SME alignment and error analysis, not just model accuracy Ability to work closely with clinical, quality, and technical stakeholders, translating feedback into system design improvements Strong judgment in communicating trade-offs and risks, particularly in regulated environments Qualifications
Bachelor's degree with 9+ years of experience, or Master's degree with 6+ years of experience Strong expertise in Python, SQL, and machine learning frameworks Experience with vector databases and modern AI architectures Hands-on experience with cloud platforms (AWS and/or Azure) Proven ability to build and deploy scalable data and AI solutions in production environments Core Competencies
Technical Expertise Deep knowledge of data science, machine learning, and AI/LLM systems Ability to design scalable, production-grade architectures Business Acumen Understands how data and AI drive business outcomes Aligns technical solutions with organizational goals Leadership Mentors team members and leads cross-functional initiatives Acts as a subject matter expert Problem Solving Solves complex, ambiguous problems with innovative approaches Applies critical thinking across multiple data sources and constraints Communication Clearly explains complex technical concepts to non-technical stakeholders Builds alignment across teams and functions Quality & Compliance Ensures adherence to all quality systems and regulatory requirements Integrates quality and compliance into all aspects of work
Languages
- English
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