Trinity is seeking an Engagement Manager to join our growing Analytics organization with a focus on delivering data and AI-enabled analytics solutions. This role blends strong client leadership, analytics execution, and practical application of AI (including GenAI and LLM-based approaches) across commercial use cases.

Trinity is a 1400-person, global organization that partners with ~350 life sciences companies annually. At the highest level, we provide Strategy, Insights, and Analytics support. Within Analytics, we have well-established SME verticals (e.g., forecasting, sales analytics, commercial data solutions, data science, AI/ML).

Trinity is investing in expanding our Analytics Strategy team, a seller-doer group that owns client relationships and overall account delivery. Engagement Managers are accountable leaders responsible for commercial growth, delivery excellence, and talent development, while helping scale Trinity’s AI-enabled analytics capabilities.

This is a unique opportunity to join an established firm and work in an entrepreneurial environment, building and scaling a fast-growing team within a core strategic priority area for Trinity.

We are looking for experienced analytics talent with a proven ability to:

• Sell, manage, and deliver a book of business
• Act as thought leaders in technology solutions and/or integrated analytics that address specific commercial pharma/biotech needs (e.g., customer engagement, forecasting, insights democratization)
• Build strong teams, collaborate cross-functionally, and contribute to internal development and growth of innovative capabilities

Essential Functions

Client & Project Delivery

Our Analytics Strategy team serves as the “tip of the spear” as client-embedded leaders with deep understanding of client needs and analytics methodologies. They have a deep understanding of client portfolio, therapeutic landscape, and analytics + technology capabilities with a broad analytics repertoire. This role:

• Serves as the day‑to‑day client contact for analytics engagements—supporting discussions, participating in presentations, and ensuring high-quality deliverables.
• Translates client business questions into practical, analytics and AI‑driven approaches across forecasting, sales analytics, omnichannel measurement, and data science.
• Manages execution of project activities, including timelines, workplans, stakeholder coordination, deliverable development, and solution hand‑offs.
• Maintains accountability for project quality, accuracy, and consistency across all workstreams.
• Surfaces risks or scope changes early and guide clients through potential solutions or adjustments.

Business Development Support

• Identify opportunities to expand existing client engagements by recognizing emerging needs or gaps.
• Support proposal development by contributing to scopes of work, methodologies, timelines, and materials.
• Participate in thought‑leadership‑aligned initiatives when appropriate (e.g., internal points of view, methodology playbooks, capability development).

Team Leadership & Development

• Oversee and coach junior team members in day‑to‑day analytics tasks, project execution, and professional development.
• Provide guidance on analytical methodologies, data structures, and tools.
• Support the development of internal best practices, training materials, and process improvements.

Internal Collaboration & Influence

• Collaborate closely with forecasting, data science, product, and data solutions SMEs to bring the right expertise to each engagement.
• Contribute to internal initiatives such as process improvement, training content, or product/tool enhancements.
• Model strong project leadership behaviors: structured problem‑solving, expectation setting, quality control, and effective client communication.

Qualifications

Education

• Bachelor’s degree required; advanced degree a plus.
• Quantitative or life‑sciences‑related fields preferred (e.g., health sciences, analytics, engineering, economics, statistics, marketing).

Work Experience

• 4–7 years of experience in life sciences analytics, consulting, or related fields.
• Experience with commercial pharma datasets, advanced analytics applications, omnichannel measurement, marketing analytics, or technology‑enabled solutions is preferred.

Skills

• Strong analytical and structured problem‑solving abilities.
• Foundational understanding of AI, LLMs, and life sciences real-world data
• Excellent communication skills (written and verbal).
• Ability to independently manage multiple workstreams and deadlines.
• Strong collaboration and stakeholder‑management capabilities.
• Proficiency with Microsoft Office Suite.