TraceLink is the world’s only integrated digital supply network for the life sciences industry, today utilized by more than 1,000 pharmaceutical companies, healthcare organizations, and 270,000+ of their trading partners to ensure that safe medicines reach the patients who rely on them. Since 2009, TraceLink has developed the market’s leading suite of serialization, track-and-trace, and information exchange software solutions, which are responsible for serializing and digitalizing information for billions of units of prescription drug products each year.
As the General Manager, Intelligent Supply Network, you will own the overall strategy, business operations, and P&L for all TraceLink solutions related to the use of predictive analytics, machine learning, and artificial intelligence (AI) technology. The GM, Intelligent Supply Network will report directly to the Senior Vice President, Business Management.
- Strategic Planning: You will assume leadership for defining the strategic market opportunities and overall vision for the operational pursuits of TraceLink’s Intelligent Supply Network business unit. In this capacity, you will determine how TraceLink applies machine learning, AI, and predictive analytics to solve complex supply chain and healthcare problems by releasing transformative data solutions in partnership with TraceLink customers
- Product Offering Development: You will utilize your subject matter expertise in partnership with the General Managers for TraceLink’s Track and Trace Compliance, Smart Supply and Logistics, Digital Health, and Digital Supply Chain Platform business units to engage TraceLink customers in order to define high-value commercial, supply chain, manufacturing, and digital health use cases for serialization and network data. You will partner with Product Management leadership to ensure that overall “customer voice” is integrated into new solution design, and you will ensure that all new data solutions are based on transparent, permissioned information sharing models in use on the TraceLink Network
- Business Development & Go-to-Market Execution: You will direct cross-functional business development activities to ensure that commercial execution results in the achievement of business unit goals (strategic, financial, product, and otherwise); you will serve as TraceLink’s leading authority on the utilization of predictive analytics, machine learning, and artificial intelligence technologies for the life sciences supply chain, and you will be expected to engage customers and speak at public events on a frequent basis
- Business Unit Ownership: You will be responsible for developing annual operating plans for the Intelligent Supply Network business unit, and you will manage the Profit and Loss statement in conjunction with Finance business partners to ensure that business unit investments are achieving operational and financial goals
- 10+ years of relevant operational experience in fast-paced pharmaceutical, life sciences consulting, or high tech environments, with SaaS experience preferred
- Demonstrated understanding of and experience in applying data/analytics models to commercial supply chain problems and use cases
- Demonstrated leadership and strategic planning skills, preferably in high-growth, matrixed or cross-functional settings
- Exceptional written and communication skills, and the ability to translate complex topics in analytics, machine learning, and artificial intelligence into customer-centric use cases that will engage C-level executives
- Ability to think strategically about multi-dimensional challenges facing the global pharmaceutical and healthcare supply chain and the ways in which new business models and the application of advanced machine learning and/or artificial intelligence may unlock value within a digital supply network
- Demonstrated consultative approach to engaging with customers to gather feedback which can be translated into product requirements for innovative, ROI-driven solution use cases
- Inherent intellectual curiosity and desire to learn about new technologies and how they may be applied to solve critical, real-world problems in supply chain and healthcare environments