Sr. Specialist – Business Insights & Analytics, Advanced Analytics - US Vaccines & Id

Merck Merck · Pharma · NJ

This role focuses on applying advanced analytics, Machine Learning, NLP, Generative AI, and Agentic AI frameworks to generate actionable insights for commercial decisions in the pharmaceutical/biotech/healthcare industry. It involves leveraging LLMs, RAG, autonomous agents, and multi-agent orchestration to enhance insight generation and automate analytical workflows, with a secondary focus on data engineering for these applications.

What you'd actually do

  1. The Sr. Specialist will partner with cross‑functional teams to design and deliver scalable analytical solutions aligned with business priorities, including the application of Machine Learning, Natural Language Processing, Generative AI (GenAI), and emerging Agentic AI frameworks to accelerate insight generation and automate routine analytical workflows.
  2. This may include leveraging LLM‑based retrieval‑augmented generation (RAG), autonomous agent pipelines, prompt‑driven analytics, and multi‑agent orchestration to enhance efficiency and analytical depth.
  3. The Sr. Specialist may also play a key role in measuring the impact of promotional programs and providing recommendations on how best to optimize future promotional spend through data-driven insights.
  4. Understand the internal stakeholder business needs and priorities to build analyses that promote business objectives by providing actionable insights.
  5. Analyze data using advanced analytical/statistical techniques across disparate databases/sources (including claims/EMR Data and other sources) to develop insights drive to inform the commercial business strategies.

Skills

Required

  • Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Data Science, etc.)
  • 3 years of relevant experience delivering complex analytical projects in the pharmaceutical/biotech/healthcare industry
  • Proficiency in database management systems and modeling languages preferred (Python, SAS, SQL) as well as expertise with Microsoft Excel and PowerPoint
  • Self-motived, proactive mindset, and ability to work independently
  • Strong interpersonal and communication skills to interact with diverse teams and stakeholders
  • Strong organizational and time management abilities, capable of navigating a complex matrix environment
  • Proven data science skills leveraging advanced statistical methods, Machine Learning/Artificial Intelligence, Natural Language Processing (NLP) modeling and model evaluation
  • Experience or strong familiarity with Generative AI (GenAI) concepts, including: Large Language Models (LLMs), prompt engineering, retrieval‑augmented generation (RAG), Model fine‑tuning, embedding models, vector databases (e.g., FAISS, Pinecone), Evaluation frameworks for LLM outputs (hallucination detection, grounding, safety)
  • Exposure to Agentic AI frameworks, such as: Multi‑agent orchestration frameworks (e.g., LangGraph, LangChain Agents, Semantic Kernel planners), Workflow/automation agents for data pipelines, monitoring, anomaly detection, Tools enabling autonomous task execution (planning, reasoning, tool‑calling agents)

Nice to have

  • Python
  • SAS
  • SQL
  • Microsoft Excel
  • Microsoft PowerPoint

What the JD emphasized

  • Experience or strong familiarity with Generative AI (GenAI)
  • Exposure to Agentic AI frameworks

Other signals

  • application of Machine Learning, Natural Language Processing, Generative AI (GenAI), and emerging Agentic AI frameworks
  • leveraging LLM‑based retrieval‑augmented generation (RAG), autonomous agent pipelines, prompt‑driven analytics, and multi‑agent orchestration
  • Experience or strong familiarity with Generative AI (GenAI) concepts
  • Exposure to Agentic AI frameworks