Digital Technology Lead – Data and AI

Join Us in Tackling Autoimmune Disease at Its Root

At Vor, we believe science can do more than manage symptoms. It can change the course of disease. By advancing telitacicept, a first‑and potentially best‑in‑class dual BAFF/APRIL inhibitor, we are silencing upstream survival signals and stopping downstream autoimmune cascades. Together, we are addressing disease at its root cause and rewriting what is possible for patients worldwide.

When you join Vor, you’re not just working on a medicine. You’re part of a mission to redefine the future of autoimmune care.

Impact:
Contribute directly to a medicine with best‑in‑disease Phase 3 results in myasthenia gravis and expansion into multiple autoimmune diseases.

Growth:
Be part of a rapidly scaling company with opportunities to grow your career in science, clinical development, commercial strategy, and beyond.

Innovation:
Work on a platform with potential beyond one indication — a therapy that has already shown consistent results across lupus, IgA nephropathy, and Sjögren’s syndrome.

Belonging:
Join a culture where every voice is heard, and where our shared mission unites us across functions and geographies.

Location:
Boston, MA preferred

The Digital, Data, and Technology (DD&T) organization seeks a Director‑level Data and AI Lead to define and scale enterprise data and AI capabilities in a fast‑moving biotech environment. This role will establish the AI and data strategy and technical foundation needed to support clinical, regulatory, medical affairs, commercial, and executive decision‑making as the company advances toward commercialization.

The Director will serve as both strategic leader and hands‑on builder, partnering across functions and vendors to deliver practical data governance, reporting, and AI use cases that improve productivity, visibility, cycle time, and business decisions.

• AI strategy and roadmap: Develop and execute a pragmatic AI roadmap focused on productivity, business acceleration, and responsible use; prioritize a small number of high‑value use cases based on business value, feasibility, readiness, and risk.
• Enterprise productivity enablement: Lead adoption of AI tools such as Microsoft Copilot, ChatGPT Enterprise, or other approved platforms.
• Business‑outcome use cases: Identify, scope, and deliver focused AI and analytics use cases that improve business outcomes, such as dossier readiness, writing acceleration, clinical operational visibility, proactive monitoring, site engagement, SOP and policy drafting, contract review support, and functional knowledge assistants.
• Regulated data and AI controls: Partner with Quality, Legal, Information Security, and business owners to ensure data and AI solutions are secure, compliant, appropriately governed, and aligned with GxP, privacy, data integrity, and inspection‑readiness expectations where applicable.
• Data strategy: Define and own the enterprise data technology strategy aligned to company priorities, clinical development goals, commercialization readiness, and digital operating model.
• Data foundation and architecture: Design and implement a scalable data infrastructure that integrates internal and external data sources across clinical, regulatory, medical affairs, commercial, finance, and operational domains.
• Clinical‑to‑commercial reporting: Build the data capabilities required to support consistent operational and analytical reporting, including clinical trial performance, regulatory readiness, medical affairs activity, launch readiness, commercial insights, and executive dashboards.
• Cross‑functional partnership: Serve as the bridge between business functions, technology teams, vendors, and leadership; translate business needs into data products, analytics solutions, AI capabilities, and implementation roadmaps.
• Operating model and delivery: Establish delivery practices, intake processes, success metrics, portfolio prioritization, and governance forums to ensure data and AI work is focused, transparent, and outcome‑driven.

• Bachelor’s degree in Computer Science, Data Science, Information Systems,…