Senior Specialist, AI Innovation Consultant

Merck•Rahway, NJ

1d•Hybrid

About The Position

The Opportunity: Based in Rahway, New Jersey, join a global healthcare biopharma company and be part of a 130-year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. Be part of an organization driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. Drive innovation and execution excellence. Be a part of a team with a passion for using AI to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats. Role Overview: As an AI Innovation Consultant, you will serve as a core analytical resource within the AI Innovation Studio, partnering closely with the AI Innovation Studio leads to evaluate, shape, and validate AI opportunities across the enterprise. In this role, you will analyze business processes, synthesize research findings, build value cases, and produce the structured assessments that inform Opportunity Assessments and downstream PoC planning. This role is highly research- and analysis-oriented. You will contribute directly to stakeholder research, process and workflow analysis, competitive and technology landscape scanning, and ROI modeling — producing rigorous, evidence-based outputs that enable alignment between business, AI, and delivery teams. While you will most often operate in partnership with Studio leads, you will also take ownership of specific analytical workstreams or lower-complexity assessments as appropriate.

Requirements

5+ years of experience in business analysis, strategy, technology consulting, or innovation-focused analytical roles.
Experience evaluating technology-enabled initiatives, with exposure to AI, automation, or data platforms preferred.
Track record of producing structured analytical deliverables (business cases, opportunity assessments, ROI models) in complex enterprise environments.
Research design and analytical synthesis, including the ability to structure ambiguous problems into clear analytical frameworks.
Strong quantitative and qualitative reasoning, with comfort building financial models, value cases, and data-driven recommendations.
Ability to clearly document business challenges, desired outcomes, and supporting evidence for audiences.
Solid understanding of technology value propositions, including AI/GenAI, data platforms, cloud services, and automation.
Ability to critically assess technical feasibility and engage technical partners with informed, evidence-based questions.
Familiarity with Agile and iterative delivery approaches.
Highly detail-oriented and intellectually rigorous, with comfort operating across multiple concurrent analytical workstreams.
Strong written and verbal communication skills and high emotional intelligence.
Organized, dependable, and effective in ambiguous, fast-moving environments.
Agile Transformation
Business Case Development
Business Process Analysis
Data Analytics
Digital Transformation Initiatives
Incident Management
ITIL Service Delivery
IT Infrastructure Management
Objectives and Key Results (OKRs)
Process Leadership
Scientific Software Development
Software Development Life Cycle (SDLC)
Technical Leadership
User Acceptance Testing Support
Writing Technical Documents

Nice To Haves

Current Employees apply HERE
Current Contingent Workers apply HERE

Responsibilities

Conduct Research & Analytical Deep-Dives: Perform structured analysis of business processes, workflows, and pain points to identify and qualify AI opportunity areas across multiple business engagements.
Gather, organize, and synthesize data from stakeholder interviews, operational metrics, industry benchmarks, and internal systems to build a fact base for each engagement.
Conduct landscape scans of relevant AI technologies, vendor capabilities, and competitive applications to inform solution shaping.
Translate Business Problems into AI-Ready Inputs: Analyze and synthesize findings from stakeholder interviews, journey maps, and user research into clear problem statements, use cases, and desired outcomes.
Document current-state workflows, user needs, pain points, and non-functional considerations required for Opportunity Assessment.
Produce clear, well-structured analytical artifacts that translate business ambiguity into actionable inputs for AI and delivery teams.
Perform Technically Grounded Opportunity Analysis: Apply a strong understanding of AI, automation, data platforms, and cloud technologies to assess feasibility, complexity, and value potential of proposed AI solutions.
Evaluate technical and data constraints by reviewing architecture documentation, data availability, and integration requirements alongside architects, data scientists, and engineers.
Ensure proposed AI opportunities are grounded in technical reality and supported by evidence prior to handoff to delivery teams.
Build Value Cases & Support PoC Planning: Own the end-to-end value case for each assessed AI opportunity — from initial data discovery and analysis through building ROI models and business cases — providing the quantitative rigor needed to validate, prioritize, and advance initiatives into PoC.
Define and document scope boundaries, assumptions, success metrics, and risk factors to support early PoC planning.
Ensure analytical outputs are complete, coherent, and decision-ready, reducing friction during transition to delivery teams.
Maintain traceability from business problem through value hypothesis to recommended path forward.
Support Stakeholder Alignment & Reporting: Build strong working relationships with business and IT stakeholders through clear communication, analytical credibility, and follow-through.
Prepare executive-ready briefings, scorecards, and summary reports that distill complex analytical findings into clear recommendations.
Contribute to positive stakeholder experiences by maintaining rigor, transparency, and momentum throughout engagements.