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Technical Consultant; Pre-Sales

Job in Kalispell, Flathead County, Montana, 59901, USA
Listing for: RELX INC
Full Time position
Listed on 2026-06-07
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer, Data Science Manager, Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: Technical Consultant (Pre-Sales)

Do you want to lead impactful presales engagements where your knowledge of AI, ontologies, and advanced analytics directly drives customer insight and business growth?

About the Team

This role sits within Elsevier’s Advanced Data Solutions team, which is responsible for selling and enabling customer implementations of Elsevier’s data and software solutions, with a particular focus on the Datasets and Sci Bite offerings.

Technical Consultants (Pre-Sales) report to the global Director of Technical Consulting (Pre-Sales) while operating in regionally aligned roles, with ownership across North America, EMEA, and APAC (primarily Japan). The team partners closely with Sales, post‑sales, and Professional Services teams to support enterprise customer engagements.

Our solutions are already deployed within the world’s top 20 pharmaceutical companies, as well as organizations across other verticals where data‑driven insight and advanced analytics are critical.

About the Role

As a Technical Consultant (Pre‑Sales), you will play a critical role in driving revenue growth by partnering with Sales to position Elsevier’s data and software solutions, and analytics capabilities as enablers of customer insight and decision‑making. You will act as the technical authority throughout the sales cycle – driving discovery, defining data use cases, and showcasing how Elsevier’s solutions power advanced analytics, knowledge graphs, and AI workflows.

Success in this role is built on three pillars – a strong technical foundation, deep domain understanding, and exceptional customer‑facing skills – enabling you to translate data and software capabilities into compelling, outcome‑driven solutions.

Responsibilities Pre‑sales solution leadership
  • Develop and maintain deep expertise in Elsevier’s solutions including datasets, semantic technology, ontology management and analytics capabilities, including how they combine to deliver customer insights
  • Lead technical discovery to understand customer objectives, analytical workflows, data landscapes, and success criteria, translating business and scientific challenges into data‑driven use cases, solution architectures, and value narratives
  • Design and deliver tailored solution demonstrations showcasing how Elsevier data and software enable insights (e.g., discovery, analytics, AI/ML readiness, and knowledge graph construction)
  • Scope and prepare solution proposals, and support proof of concepts (PoCs), technical evaluations, and pilots to validate solution fit and value, clearly articulating technical trade‑offs, assumptions, and dependencies across data, software, and services
  • Act as a trusted technical advisor throughout the sales cycle, supporting account strategy, solution positioning, and competitive differentiation
Cross‑functional alignment
  • Validate solution feasibility in collaboration with Product, Post‑Sales and Professional Services teams to ensure smooth delivery, adoption, and account growth and expansion
  • Capture customer feedback and market insights to inform product positioning, roadmap priorities, and go‑to‑market strategy in partnership with Product and Marketing teams
Requirements Technical skills
  • Strong understanding of data‑driven analytics workflows, including data ingestion, enrichment, integration, and insight generation
  • Working knowledge of Generative AI, NLP, ontologies, taxonomies, and knowledge graphs, and how these are applied to real‑world analytical use cases
  • Deep understanding of cloud and technical ecosystems (e.g., AWS, REST APIs, SFTP, HTTP, OAuth, Docker, Python etc.)
Customer facing skills
  • Proven experience delivering technical demonstrations and presentations to both technical and non‑technical stakeholders
  • Excellent communication, storytelling, and stakeholder‑management skills
  • Confidence leading complex technical discussions and navigating challenging or ambiguous customer conversations
  • Willingness to travel to customer sites and industry events as required
Domain experience & education
  • Master’s or PhD in a science or technology field, or equivalent practical experience
  • Experience working with pharmaceutical, life sciences, engineering, or other data‑intensive enterprise…
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