Director, Product – Data & Insights

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

At Thermo Fisher’s PPD clinical research business, we’re using digital innovation, data science, and AI to reimagine how life-changing therapies reach patients. Our teams combine deep scientific expertise with advanced analytics, automation, and digital platforms to make research smarter, faster, and more connected.

We know that innovation happens when diverse minds meet. Our Digital Science, Data, and AI professionals collaborate closely with scientists, clinicians, and operational experts to solve real-world challenges in clinical research. Alongside our partnership with Open AI, you can be part of the collaboration that will help to improve the speed and success of drug development, enabling customers to get medicines to patients faster and more cost effectively.

Role Overview

The Director, Product – Data & Insights is a senior leader within the Insights & Customer Experience product domain and a key member of the domain leadership team.

This role is responsible for building and leading the Data & Insights capability that powers sponsor-facing products, advanced analytics, predictive intelligence, and AI-enabled experiences. The Director will partner closely with Product Management, Engineering, Architecture, and Business leaders to ensure data is trusted, connected, and structured to support decision-making and innovation.

This is not a traditional BI, reporting, data governance or engineering role. We are seeking a hands-on data and intelligence leader who can build trusted data foundations, enable AI-driven solutions. The successful candidate will be equally comfortable defining strategy, leading technical teams, and diving into source systems, data models, and data flows to solve complex business and technical problems.

Key Responsibilities

Data Strategy & Leadership

• Define and execute the Data & Intelligence strategy for the Insights & Customer Experience product domain.
• Build and lead a Data & Intelligence Center of Excellence spanning analytics, data science, and AI enablement.
• Serve as a strategic partner to Product, Engineering, Architecture, Clinical Operations, and Business leaders.
• Establish data as a strategic product asset that drives customer value, operational effectiveness, and business outcomes.
• Influence decisions through trusted data, analytical rigor, and actionable insights.

Data Foundations & Trust

• Develop deep understanding of source systems, business processes, and end-to-end data flows.
• Define data modeling strategy and partner with Engineering and Architecture teams to deliver scalable, reusable data solutions.
• Partner with the businesses to drive confidence in the data through governance, lineage, and KPI frameworks
• Lead investigation and resolution of data quality issues, KPI discrepancies, and reporting challenges by partnering across business, product, and technology teams to identify and address root causes.

Analytics & AI Enablement

• Lead teams responsible for analytics, data science, and intelligence generation.
• Develop a comprehensive understanding of enterprise data assets and identify opportunities to connect data across systems to answer high-value business questions.
• Establish reusable data assets and analytical frameworks that accelerate insight generation and decision-making.
• Drive development of predictive analytics and decision-support capabilities.
• Define data requirements for machine learning, generative AI, and agentic solutions.
• Ensure enterprise data assets are structured and accessible to support AI-enabled products and experiences.

Qualifications

• Bachelor's degree or equivalent and relevant formal academic / vocational qualification (Advanced degree preferred).
• Previous experience in data, analytics, data science or data product leadership roles that provides the knowledge, skills, and abilities to perform the job (comparable to 10+ years’ experience). 
• 5+ years leading technical teams including data analysts, data scientists, or similar professionals. 
• Strong expertise in data modeling, data architecture, and end-to-end data flows.
• Strong SQL skills and ability to independently validate, troubleshoot, and analyze complex datasets.
• Experience with modern cloud data platforms, including Snowflake or equivalent technologies.
• Experience establishing data quality, governance, lineage, and KPI frameworks.
• Experience supporting digital products and partnering closely with Product, Engineering, and