Product Director - Evinova

AstraZeneca•Durham, NC

7d•Hybrid

About The Position

Evinova, a distinct business within the AstraZeneca group, is seeking an entrepreneurial, AI-fluent Product Director to own and build a core AI-native product area from the ground up. The role will define the product vision, strategy, and multi-year roadmap, creating solutions that change how clinical development and clinical operations teams work. It is a founding product leadership position with significant autonomy and general-manager-style ownership, but it is an individual contributor role with no direct reports. The Product Director leads a matrixed team across engineering, design, data science, and commercial through influence and clear direction. The role owns the end-to-end product lifecycle, from opportunity discovery, prototyping, and validation through development, launch, go-to-market, and post-launch iteration. It requires deep engagement with users and customers, AI and machine learning embedded throughout the product, intuitive collaborative workflows, and connectivity across Evinova modules. The Product Director also owns product success metrics and commercial outcomes, including the product area's P&L outlook and resource trade-offs, while balancing speed to market with regulatory compliance. The position is based on an office-first model, with an average minimum of three days per week in the office and flexibility respected.

Requirements

At least 8 years of product management experience.
Bachelor's degree.
At least 3 years in a director-level or senior product leadership capacity, owning a product area end-to-end.
Experience in clinical trials or life sciences, with a deep understanding of clinical development and clinical operations personas and the clinical ecosystem, including EDC, CDMS, CTMS, and eTMF.
An entrepreneurial track record that includes taking at least one product from zero to one and evidence of conceiving, shipping, and scaling products.
Hands-on experience building AI/ML-powered products, including understanding model development lifecycles, training data strategies, prompt engineering, evaluation frameworks, and AI-feature user experience.
Experience operating in enterprise B2B SaaS environments, including complex customer landscapes, long sales cycles, and platform-level product decisions.
Strong technical skills, including the ability to work directly with engineers and data scientists, review technical specifications, and contribute to architectural trade-offs.
Daily use of AI tools in personal workflows for research, analysis, writing, prototyping, and decision-making, and the ability to explain AI's impact on product development.
Ability to evaluate AI/ML outputs, reason about precision and recall trade-offs, and make product decisions about thresholds, confidence scoring, and human-in-the-loop patterns.
Current understanding of foundation models, agentic AI, retrieval-augmented generation, and fine-tuning, with a perspective on applying these capabilities in regulated clinical research.

Nice To Haves

Experience as a founder or co-founder of a technology company, or as the first product hire at an early-stage startup.
Working knowledge of clinical trial data standards, including CDISC SDTM/ADaM and CDASH, and regulatory submission workflows.

Responsibilities

Define and own the product vision, strategy, and multi-year roadmap for an AI-native product, from first principles through scale.
Develop a firsthand understanding of users, their problems, and day-to-day workflows to identify opportunities for significant impact.
Validate hypotheses rapidly through prototyping and experimentation.
Own the full product lifecycle, including concept, design, development, launch, go-to-market, and post-launch iteration informed by usage data and customer feedback.
Build AI and machine learning into the product, including capabilities such as intelligent automation, contextual recommendations, predictive insights, and generative AI-powered workflows.
Work with data science and engineering to turn AI capabilities into practical, regulation-aware product features.
Design intuitive, collaborative, end-user-focused workflows that reduce burden and connect clinical development and clinical operations teams and Evinova modules.
Support user adoption and change management for AI-enabled ways of working.
Monitor developments in clinical trials and AI and identify opportunities to apply emerging capabilities.
Coordinate with the matrixed product organization to improve connectivity across Evinova modules and inform the product roadmap.
Partner with commercial teams to avoid overfitting the product to a single customer and to iterate toward product-market fit.
Align engineering, design, data science, and commercial stakeholders around a unified product vision.
Communicate product strategy, progress, and trade-offs to executive leadership and enterprise customers.
Define and own success metrics, including adoption, engagement, revenue contribution, and clinical trial cycle-time reduction, and use data to prioritize work.
Own the product area's P&L outlook, make resource trade-offs, and drive measurable commercial outcomes.
Balance speed to market with regulatory requirements, including GxP, 21 CFR Part 11, GDPR, and HIPAA.
Cultivate partnerships with data providers and standards bodies, including CDISC and HL7 FHIR.
Promote experimentation, intellectual integrity, and continuous learning within the product area and the broader team.