Eli Lilly

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

The Lilly Small Molecule Discovery group is an organization purpose-built to create molecules that make life better for people. We focus on using cutting edge science to unlock new approaches that can treat people suffering from diseases with poor treatment options. We continually challenge ourselves to deliver molecules that can provide breakthrough efficacy with the highest possible safety margins. We are dedicated to optimizing our mindset, technology, and processes for faster, more nimble execution. Our success is built on a culture that empowers innovative problem solving through open collaboration and individual accountability.

Position Summary:

Lilly’s newly created Early Molecule Discovery (EMD) team is responsible for small molecule hit-to-lead prosecution through the judicious application of best in class and novel approaches applied to pre-portfolio targets. We seek a cheminformatics group leader with a demonstrated ability of successfully applying in silico technologies to drive the discovery of quality lead-like molecules against hard to drug therapeutic targets. This is a lead from the bench role, we therefore seek a hands-on candidate who can deftly apply cheminformatics and AI/ML technologies to impact library design, hit identification and (virtual) hit expansion efforts towards differentiated and efficacious lead molecules across multiple projects. The candidate will be highly collaborative and foster seamless collaborations with cross-functional partners to develop data-driven hypotheses and models that are leveraged by project teams to accelerate early molecule discovery efforts. The position requires excellent people skills, a positive can-do attitude and the ability to thrive in a highly interactive and fast-paced team environment.

Responsibilities:

• “Lead from the bench” by judiciously building up and applying state of the art cheminformatics, ML/AI, and advanced analyses capabilities, to enable library design, hit identification, prioritization and hit-to-lead progression across multiple target classes and modalities.
• Provide scientific leadership and strategic guidance on cheminformatics and applied ML/AI approaches to drive data driven drug discovery.
• Encourage close collaborations and initiatives with computational colleagues, medicinal chemists and other cross function partners that culminate in the generation of well poised screening collections, quality models and testable hypotheses, enhancing our ability to deliver differentiated quality hits and leads.
• Ensure team success by providing guidance on the application of modern cheminformatics, ML/AI methods for: library design (e.g. diversity, focused, bridging, fragment, DEL collections); analyzing large datasets (e.g. from HTS campaigns or omics data sets) and building predictive (active learning) models from them; data mining internal and external data-sets/bases; enabling hit prioritization and expansion efforts; guiding ligand-/fragment-based design activities.
• Provide cheminformatics insight for new target identification and evaluation initiatives in the early space across a range of targets and binding mode types.
• Proactively investigate new technologies that have the potential to accelerate EMD’s ability to prosecute challenging targets and deliver quality differentiated leads.
• The candidate will also cultivate cross pillar collaborations with new technology, and Tech@Lilly colleagues to help guide and subsequently leverage transformative hit identification and hit-to-lead approaches.
• Develop synthon-based search strategies to allow teams to leverage ever increasing virtual spaces without having to rely on brute force searches of fully enumerated spaces.
• Ensure the timely delivery of quality data, rigorous analyses and robust models to project teams to accelerate hit identification and chemical series evaluation/evolution efforts.
• To be adept at communicating results, and setting team as well as larger organizational goals and expectations.
• Engage with external teams upon the identification and elaboration of early lead molecules across multiple projects and mechanisms.

Basic Requirements:

• PhD in Cheminformatics, Computational Chemistry, or related field with 7+ years relevant research and/or industrial experience.
• Track record of successfully applying and developing cheminformatics workflows and tools that accelerate hit finding, hit expansion, lead generation and library design efforts.
• Expertise in data analytics, ML/AI modelling in the context of cheminformatics and a solid grasp of statistical principles.
• Ability to create, sustain and model a culture of innovation, collaboration and dedication.
• Strong scientific programming skills (Python essential) and experience building data visualizations and dashboards (e.g., in Spotfire).
• Demonstrated growth mindset, whilst maintaining close collaboration among computational chemistry leaders, elevating the global computational chemistry team as a whole.
• Aptitude for building inclusive teams and commitment to mentoring early career computational chemists.
• Demonstrated ability to identify and effectively champion new technologies culminating in successful drug discovery applications thereof.
• Proactive in establishing and driving effective collaborations with medicinal chemists and scientists form other disciplines to achieve project goals and timelines.
• Ability to communicate effectively with team members, cross-functional colleagues and senior leadership.
• Demonstrated ability to inspire and lead scientists to work across teams, functions and sites to achieve aspirational goals that accelerate portfolio deliveries.

Additional Preferences:

• Excellent understanding of the phases of drug discovery from target assessment through to candidate selection and the fundamental concepts of drug design, medicinal chemistry and ADME.
• Good appreciation of computational chemistry and organic chemistry.
• Familiarity with Large Language Models (LLMs).
• Experience using synthons and transformations to generate and interrogate virtual spaces.
• Demonstrated experience in working collaboratively across various disciplines to meet project goals and timelines.
• Agile and ready to change research priorities as necessary for success.
• Ability to work independently and as an integral part of a larger collaborative team.
• Highly organized with excellent analytical, documentation, time management, and multi-tasking skills.
• Views personal success as a consequence of the team’s success.
• Self-accountable for the timely delivery of progressable hits and eventual leads for uptake within the larger small molecule discovery organization.
• Self-driven, hardworking, lab first, data dependent decision maker.
• Excellent communication of goals and priorities across computational chemistry teams.

Additional Information:

Physical Demands/Travel:

The physical demands of this job are consistent with a lab environment.

The physical demands here are representative of those that must be met by an employee to successfully perform the essential functions of this job.

There will be some travel associated with this role.

Work Environment:

This position’s work environment is in a Laboratory.

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.

• To perform this job successfully, an individual must be able to perform the role and responsibilities satisfactorily. The requirements listed above are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women’s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is

$181,500 - $294,800

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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