Associate Principal, Analytics

Trinity Partners•Waltham, NY

12d

About The Position

Trinity Life Sciences is seeking an Associate Principal to join our growing Analytics team. In this role, you will oversee the delivery of high-impact analytics engagements, serve as a key client contact, and guide teams in solving complex commercial business challenges across the product lifecycle, with the opportunity to contribute to account growth and revenue. You will work closely with senior leadership and cross-functional teams to deliver actionable solutions across data orchestration, AI/ML, omnichannel, & RWE. This role offers the opportunity to oversee multiple engagements, expand client relationships, and contribute meaningfully to the growth of Trinity's Analytics capabilities. 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. Associate Principals 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 a thought leader in technology solutions and/or integrated analytics that address specific commercial pharma/biotech needs (e.g., customer engagement, forecasting, insights democratization), and build strong teams, collaborate cross-functionally, and contribute to internal development and growth of innovative capabilities.

Requirements

Bachelor’s degree required
7–9 years of experience in life sciences analytics, consulting, or related fields.
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.

Nice To Haves

Advanced degree a plus.
Quantitative or life‑sciences‑related fields preferred (e.g., health sciences, analytics, engineering, economics, statistics, marketing).
Experience with commercial pharma datasets, advanced analytics applications, omnichannel measurement, marketing analytics, or technology‑enabled solutions is preferred.

Responsibilities

Identify and drive opportunities to expand existing client engagements by recognizing emerging needs or gaps.
Drive proposal development by crafting 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).
Serve as a key client contact for analytics engagements—supporting discussions, participating in presentations, and ensuring high-quality deliverables.
Translate client business questions into practical, analytics and AI‑driven approaches across forecasting, sales analytics, omnichannel measurement, and data science.
Oversee execution of project activities, including timelines, workplans, stakeholder coordination, deliverable development, and solution hand‑offs.
Maintain accountability for project quality, accuracy, and consistency across all workstreams.
Surface risks or scope changes early and guide clients through potential solutions or adjustments.
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.
Drive development of internal best practices, training materials, and process improvements.
Collaborate closely with forecasting, data science, product, and data solutions SMEs to bring the right expertise to each engagement.
Lead internal initiatives such as process improvement, training content, or product/tool enhancements.
Demonstrate strong project leadership behaviors: structured problem‑solving, expectation setting, quality control, and effective client communication.