Data Scientist/AI Engineer

LucyRx

About The Position

We are seeking a Data Scientist/AI Engineer to develop predictive analytics, machine learning models, and AI-driven solutions that support clinical, operational, and financial initiatives across the pharmacy benefits ecosystem. This role works cross-functionally to identify opportunities, build data products, and translate insights into business impact. In addition to traditional data science responsibilities, this position plays a key role in designing agentic workflows, integrating LLM-powered tools, and building automation that operationalizes AI throughout the organization. The role collaborates closely with the AI team to design, maintain, and continuously improve intelligent systems and AI-enabled processes.

Requirements

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.
3+ years of professional experience in data science or machine learning engineering.
Strong Python (preferred) or R skills, including experience with modern ML/AI libraries.
Advanced SQL experience and comfort working in Snowflake, Azure Data services, and other cloud data platforms.
Hands-on experience with data visualization tools such as Power BI or Tableau.
Strong understanding of traditional machine learning, feature engineering, and statistical methodology.
Familiarity with LLM workflows, embeddings, vector stores, RAG, or modern AI architecture.
Experience with version control, preferably in Azure Repo or directly in Git

Nice To Haves

Experience implementing agentic AI workflows, LLM-based tools, or AI orchestration frameworks.
Experience with Azure AI, Azure ML, Databricks, or similar environments.
Understanding of data governance, PHI/PII data handling, and HIPAA compliance within the healthcare domain.

Responsibilities

Build, validate, and deploy predictive and machine learning models supporting PBM operations.
Work with enterprise data sources including Snowflake, Azure, and Oracle Fusion.
Develop data pipelines, transformations, and analytical workflows to support real-time and batch processing.
Create dashboards, reports, and analytical artifacts using Power BI or Tableau.
Collaborate with internal business units to identify opportunities for data science and AI integration.
Translate analytics and model outputs into actionable recommendations that support strategic decision-making.
Design, build, and refine agentic workflows and LLM-based applications, leveraging frameworks such as LangChain, Semantic Kernel, or Azure AI Studio.
Implement AI agents capable of task automation, retrieval-augmented generation (RAG), and enterprise workflow orchestration.
Evaluate emerging AI technologies and prototype new capabilities for future deployment.
Work with the AI team to build scalable, reliable, and secure AI systems.