Associate Director - Competitive Analytics

Responsibilities: 

Competitive Analysis: 

• Co-lead data integration and analytical frameworks: Develop and implement a structure that connects multiple data sources together to enable improved data quality, optimize analytical capabilities, and enable broad industry trend analyses to produce actionable competitive intelligence that informs portfolio strategy.    

• Generate competitive value insights from across the industry:  Develop and prosecute hypotheses for different strategies that competitors are leveraging to invest in and deliver their portfolio, develop capabilities, and maximize their value and productivity.  

• Build and sustain valuable partnerships to drive strategy: Collaborate across the portfolio strategy team to support competitive insight projects with competitive analytics on an ongoing basis. Collaborate with key LRL and BU stakeholders for input on analytical conclusions and communications, incorporating feedback to develop new analyses and reporting capabilities. 

• Leverage storytelling to communicate & influence: Tailor clear, concise, and compelling messages adapted to each audience. Communicate analyses to key customers beyond the portfolio strategy organization (e.g. figures, tables, and verbal conclusions to scientists, project teams and leadership). Demonstrate mastery of the subject matter, attention to detail and an ability to professionally defend the analyses and conclusions. 

Data management and process improvement: 

• Partner with Decision Sciences and Analytics staff to monitor and communicate progress towards sustainability goals for our portfolio, including speed, success rates, and value creation. 

• Deliver excellent portfolio review content, ensuring the accuracy of information with high attention to detail reported for pipeline progression and value analyses. 

• Own the creation and sustainability of data analytics principles, integrating into competitive intelligence processes with a continuous improvement mindset. 

• Serve as the functional SME/champions for information/data sharing platforms (e.g. Minerva, Penumbra, VITAL, etc.), improving the awareness and availability of competitive intelligence information.  

• Represent competitive analytics on cross-functional data, system, and analytical improvement initiatives (e.g. Polaris, Prism,). 

• Design data systems and databases for continuous analytical improvements, including coaching colleagues on best practices to maintain these systems and databases. 

• In close collaboration with the Portfolio Strategy Decision Sciences team, maintain the internal pipeline database for key peer-set companies and Lilly programs, including connection with Polaris. Lead and improve the overall data update process, partnering with colleagues managing the external data updates, to drive a focus on data integrity, attention to detail, and efficiency. 

• Anticipate and lead functional improvement efforts, including process updates and new analytical frameworks, to enable faster and more efficient work to meet evolving business needs. 

Basic Qualifications: 

• Bachelors Degree in a health-related, scientific or engineering field 

• Experience in the pharmaceutical business, R&D processes, and scientific concepts to contextualize analyses and establish credibility to customer base, peers and management. 

• 5+ years of experience in one or more business analytics and visualization tools including (but not limited to) SQL, VBA, Power BI, Python, or R, etc that enable production of data-driven analyses and insights from competitor data.  

• Qualified candidate must be legally authorized to be employed in the United States. Lilly does not anticipate providing sponsorship for employment visa status (e.g., H-1B or TN status) for this position.     

Additional Skills/Preferences: 

 Advanced degree in life sciences and/or business/finance 

• Degree or formal training in IT or computer science 

• Combined fluencies in the life sciences, and business / finance analytics. 

• Excellent analytical and creative problem-solving skills. Ability to identify and pursue alternative paths of inquiry for challenging questions. Comfortable with ambiguity and uncertainty. 

• Ability to connect sets of data through data translation. A general understanding of database design, data ingestion through APIs, text mining, or other advanced data manipulation capabilities,  

• Strong communication and presentation skills with the ability to simplify and articulate the \ complex 

• Demonstrated Team Lilly mindset and collaborative approach, including a track record of strong teamwork practices and achieving success by working with others. 

• Ability to effectively prioritize work and deliver on time-sensitive requests.  

• High learning agility; able to quickly grasp new concepts and absorb large amounts of information under time pressure. 

• Skilled in searching out information from both traditional and non-traditional sources, all within the guidelines of our policy.  Ability to work with multiple sources of incomplete data sets and synthesize a “true” understanding of our competitors’ strategies.