Lead Data Scientist

Position Overview

We are seeking an expert-level Lead Data Scientist to drive enterprise AI/ML, GenAI, LLM Ops, Agentic AI, and autonomous agent initiatives for our US Healthcare Revenue Cycle Management (RCM) platform. This Individual Contributor (IC) role focuses on hands-on technical leadership, building scalable, production-ready AI/ML models, autonomous agents, and predictive/analytical pipelines across RCM modules such as Claims, Prior Authorization, Coding, Collections, Scheduling, and EDI.

The role blends deep AI/ML expertise with data strategy, cloud-native deployment, RPA integration, and compliance governance, enabling intelligent automation and data-driven decision – making at scale.

Job Roles & Responsibilities

AI/ML & Agentic AI Development:

• Lead design, development, and deployment of advanced ML/DL models, LLM-based solutions, and Agentic AI workflows.
• Build autonomous agents, multi-agent orchestration pipelines, and GenAI applications for RCM operations.
• Conduct feature engineering, model validation, hyperparameter tuning, and optimization for production-level performance.
• Integrate AI models with RPA, microservices, APIs, and cloud pipelines for automation.

Data Engineering & Pipeline Oversight:

• Collaborate with data/ETL engineers to design scalable batch and real-time pipelines for training and production.
• Ensure data quality, preprocessing, lineage, and regulatory compliance (HIPAA, SOC 2, GDPR).
• Optimize data pipelines feeding AI/ML models, autonomous agents, and analytics dashboards.

MLOps / LLM Ops

• Implement CI/CD pipelines, model versioning, monitoring, rollout/rollback strategies, and safe deployment for autonomous agents.
• Collaborate with cloud teams to build scalable AI/ML infrastructure on AWS SageMaker/Bedrock, Azure ML, or GCP AI.
• Maintain audit logs, governance frameworks, and performance monitoring for LLMs, GenAI, and agentic workflows.

Analytics & Insights:

• Develop predictive, prescriptive, and generative analytics for RCM processes.
• Design and maintain dashboards, KPIs, and reports for operational, compliance, and business teams.
• Provide actionable insights enabling AI-driven automation and improved operational efficiency.

Collaboration & Mentorship

• Serve as technical IC mentor to junior data scientists and analysts.
• Collaborate with AI/ML engineers, RPA developers, DevOps, product, and business teams on cross-functional initiatives.
• Establish and enforce best practices for model development, deployment, and agentic AI workflows.

Candidate Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
• 8–12+ years of experience in data science, AI/ML, GenAI, LLM Ops, and healthcare analytics.
• Proven expertise in Agentic AI, multi-agent orchestration, and autonomous agent development.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and production deployment of AI models.
• Strong knowledge of HIPAA, SOC 2, GDPR, and compliance frameworks in healthcare..

Technical Expertise:

• Programming: Python, R, SQL, Scala
• AI/ML Frameworks: TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers
• GenAI / LLM Ops / Agentic AI Platforms
• Data Engineering: Spark, Hadoop, Snowflake, Redshift, BigQuery, Airflow, dbt
• Cloud Platforms: AWS (SageMaker, Bedrock), Azure ML, GCP AI/ML
• RPA Integration: UiPath, Automation Anywhere, Blue Prism
• CI/CD & DevOps: Docker, Kubernetes, MLOps/LLMOps pipelines
• Analytics & Visualization: Tableau, Power BI, Looker (preferred)

Skillset:

• Strong analytical, problem-solving, and modeling skills for large-scale healthcare datasets.
• Expertise in autonomous AI agents, GenAI, multi-agent orchestration, and RCM automation.
• Ability to deliver production-ready, compliant, and scalable AI/ML solutions independently.
• Excellent collaboration, communication, and technical mentorship skills.  Detail-oriented, compliance-first mindset, and strategic thinking.

Strategic Impact:

• Deliver production-ready AI/ML models, autonomous agents, and predictive analytics across RCM modules.
• Enable data-driven decision-making, AI automation, and operational excellence.
• Ensure scalable, compliant, and high-performance AI systems within the organization.
• Serve as the technical authority for AI/ML, GenAI, LLM Ops, and Agentic AI adoption in healthcare RCM.

Note: At Credence, we uphold the highest standards of integrity in our recruitment process. We do not charge any fees at any stage of the hiring process, and we strictly prohibit any third parties, vendors, or individuals from soliciting money in exchange for job opportunities at Credence.

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