Technical Pre-Sales Consultant, Professional Services

This is a fully remote position, open to applicants in New Jersey, +5 more states.

📋 Description

• Develop and maintain a deep understanding of Elsevier’s curated datasets, data APIs, integration options, MCP servers, AI agents, and SciBite semantic solutions.

• Lead technical discovery sessions to comprehend customer objectives, analytical workflows, data landscapes, and criteria for success.

• Convert business and scientific challenges into data-driven use cases, solution architectures, and value propositions.

• Design and present customized solution demonstrations.

• Define the scope and prepare comprehensive solution proposals.

• Assist with proof-of-concepts, technical assessments, and pilot projects.

• Explain technical trade-offs, assumptions, and dependencies across data, software, and services.

• Serve as a trusted technical advisor throughout the sales process.

• Support account strategy, solution positioning, and competitive differentiation.

• Counsel customers on leveraging AI advancements with Elsevier data.

• Utilize AI tools to enhance the efficiency and quality of demonstrations, proposals, and proof-of-concepts.

• Confirm solution feasibility with Product and Professional Services teams.

• Gather customer feedback and market insights to guide product positioning, roadmap priorities, and go-to-market strategies.

• Collaborate effectively with Sales, post-sales, Professional Services, Product, and Marketing teams.

⛳️ Requirements

• Profound understanding of data-driven analytics workflows, encompassing data ingestion, enrichment, integration, and insight generation.

• Practical knowledge of Generative AI and LLM-based solutions, including RAG, prompt design, agentic workflows, evaluation, responsible AI, and data governance.

• Familiarity with NER, ontologies, taxonomies, and knowledge graphs applied in real-world analytical scenarios.

• Proficient understanding of cloud and technical ecosystems, such as AWS, REST APIs, SFTP, HTTP, OAuth, Docker, and Python.

• Acquainted with AI platforms, tools, and integration patterns, including LLM APIs and MCP.

• Degree in a science, technology, or data discipline, or equivalent practical experience.

• Experience in data-intensive enterprise environments like technology, engineering, pharmaceuticals, or life sciences.

• Eagerness to learn about scientific domains.

• Awareness of how data and software facilitate research, analytics, and decision-making processes.

• Proven track record in delivering technical demonstrations and presentations to both technical and non-technical audiences.

• Outstanding communication, storytelling, and stakeholder management abilities.

• Confidence in leading complex technical discussions and navigating challenging or ambiguous customer interactions.

• Willingness to travel to customer locations and industry events as necessary.

🏝️ Benefits

• Flexible working arrangements.

• Wellbeing programs.

• Shared parental leave.

• Study assistance.

• Sabbaticals.

• Medical, dental, and vision insurance.

• 401(k) plan with matching contributions.

• Employee Share Purchase Plan.

• Wellness platform access.

• Headspace subscription.

• Employee Assistance Programs.

• Short- and long-term disability coverage.

• Life insurance.

• Accidental death insurance.

• Critical illness coverage.

• Hospital indemnity insurance.

• Parental leave policies.

• Support for adoption and surrogacy.

• HSA, FSA, dependent care, and commuter benefits.

• Paid time off.

• Days for volunteer work and participation in Employee Resource Groups.

• Country-specific benefits.