Eli Lilly

Chemical Reactivity Landscape, Scientific Project Leader

Eli Lilly • $177K — $308K *
San Francisco, CA 94112In-Person
Pharmaceuticals & Biotech
8 - 10 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Ph.D. in Chemistry or related field with 10+ years of experience; or M.S./B.S. with 15+ years in industry.
  • Expertise in synthetic and high-throughput experimentation (HTE) chemistry affecting reactivity decisions.
  • Experience in applying machine learning to chemical data for predictions of reaction outcomes and conditions.
  • Proven track record in leadership, managing scientists across different career stages.
  • Experience in owning a scientific platform from inception to deployment, focusing on user impact.

Responsibilities

  • Define the scientific vision for the Chemical Reactivity Landscape in collaboration with SIT.
  • Develop a sequenced plan translating scientific goals into measurable milestones for leadership communication.
  • Allocate resources effectively to address priority scientific questions.
  • Define theoretical and experimental strategies in partnership with computational chemistry teams.
  • Lead efforts in reaction discovery by determining valuable substrate and condition spaces for exploration.
  • Oversee the integration of foundation models and automation into reaction discovery processes.
  • Establish model evaluation standards to ensure scientific rigor and reproducibility.

Benefits

  • Opportunities for professional growth and development.
  • Participation in cutting-edge research at the intersection of chemistry and machine learning.
  • Access to state-of-the-art laboratory and computational facilities.
  • Collaborative and inclusive team culture that values scientific input and innovation.
  • Engagement with external academic and industry partners to enhance research impact.
Full Job Description
This is a hands-on scientific leadership role working at the intersection of quantum chemistry, machine learning, high-throughput experimentation, and laboratory automation. You will set the modeling strategy across mechanistic, quantum chemical, statistical, and learned approaches; direct the synthetic organic core that gives those models something real to learn; and drive the closed loop in which predictions select experiments and experimental results improve predictions. You will also decide how foundation models and agentic systems are used in reaction discovery.

The project is run in close partnership with the Synthetic Innovation Team (SIT) in Lilly Small Molecule Discovery (LSMD). SIT identifies, defines, and solves the synthetic bottlenecks that matter to the portfolio and brings new methodologies to the bench.

The role is on-site in South San Francisco with both people and project leadership scope.

Key Responsibilities

Scientific Direction & Project Leadership
  • Own the scientific vision for the Chemical Reactivity Landscape: working with the Synthetic Innovation Team (SIT) in LSMD, define what the landscape must predict, to what accuracy, for which chemistry, and in what sequence it is built
  • Translate scientific ambition into a sequenced plan with dated milestones and decision points, and communicate progress, trade-offs, and risk to senior R&D leadership
  • Secure and allocate compute, HTE capacity, and headcount against the highest-value scientific questions


Reactivity Science & Modeling
  • Partner with computational chemistry, jointly defining the level of theory, conformational sampling, transition-state treatment, and solvation strategy suited to the scientific question at hand
  • Drive descriptor and representation strategy so that models generalize across chemotypes and reaction classes, and so that their predictions can be explained in chemical terms
  • Lead catalysis-and other reaction discovery and optimization efforts defining the substrate and condition spaces worth searching
  • Maintain deep command of the primary literature across organic chemistry, machine learning, and computational chemistry, quickly judging which advances are worth bringing inside


Autonomous Experimentation & Closed-Loop Discovery
  • Set the direction for integrating foundation models and agentic systems into reaction discovery, agents that plan calculations, propose conditions, dispatch experiments to automated and cloud laboratories, and interpret the readouts that come back
  • Drive the closed loop between prediction and experiment so that HTE campaigns are selected by the model and their results measurably improve it
  • Champion low-friction and conversational interfaces that put reactivity models in the hands of bench chemists without requiring them to become modelers
  • Partner with automation, HTE, and analytical leadership so that experiments produce structured, model-ready, traceable data by default rather than by retrofit


Evaluation, Rigor & Scientific Standards
  • Establish how models and agents are evaluated before they influence experiments: benchmarks, held-out data, fair expert and random baselines, calibrated uncertainty, and documented failure modes
  • Treat scientific evaluation of foundation models as a first-class discipline rather than a post-hoc check, and build the harnesses and reference datasets that make it routine
  • Establish reproducibility, data provenance, and clear reporting of each model's domain of applicability


Team Leadership & Development
  • Lead, manage, and develop a team of computational and data scientists across career stages, including the Reaction Informatics individual contributors on this project: set clear expectations, give direct feedback, and create the conditions for high performance
  • Lead the matrixed cross-functional project team through scientific credibility and clarity of direction rather than authority
  • Mentor and coach scientists at all levels, and give people genuine scientific territory to own and grow into
  • Recruit, hire, and onboard across career stages, and invest in early-career scientists as part of the long-term talent pipeline for reactivity modeling at Lilly
  • Actively build inclusive team relationships and ensure all team members have appropriate access to challenging work, development opportunities, and visibility
  • Foster digital fluency beyond the immediate team: encourage experimentation with new tools, support training opportunities, remove barriers to adoption, and recognize scientists who use these capabilities to accelerate real chemistry


Collaboration, Influence & External Engagement
  • Partner with the Synthetic Innovation Team, medicinal chemistry, process chemistry, analytical sciences, and automation to turn portfolio bottlenecks into well-posed scientific questions
  • Engage LSMD project teams directly to understand their synthetic bottlenecks, and bring an enterprise mindset - proactively connecting teams to reactivity predictions, AI/ML-assisted retrosynthesis, and emerging technologies beyond the immediate scope of any one program.
  • Represent the project in internal governance bodies, scientific forums, and cross-functional decision-making
  • Build and manage external collaborations with academic groups, consortia, and technology partners, and evaluate them for strategic fit rather than novelty
  • Publish and present in leading chemistry, cheminformatics, and machine learning venues, and use that visibility to attract talent and partners


Safety, Quality & Compliance
  • Keep safety as the top priority; provide guidance on HSE related to new technology deployment, and laboratory operations
  • Ensure the team maintains rigorous documentation, data integrity, and compliance standards across all computational and experimental work


What Success Looks Like
  • The reactivity landscape is the default reference for condition selection across LSMD, and its uncertainty estimates hold up under real use
  • Optimization campaigns reach target conditions in measurably fewer experiments than expert-designed baselines, across multiple reaction classes
  • Models generalize to out of domain chemistry, and know precisely where they stop working
  • Autonomous and semi-autonomous campaigns run reliably against real instruments, with the loop closing without manual intervention
  • Evaluation standards set by this project are adopted by other AI-for-science efforts across Lilly


Basic Qualifications
  • Ph.D. in Chemistry or a closely related field with 10+ years of relevant experience; or M.S./B.S. with 15+ years of relevant industry experience
  • Deep expertise in synthetic and HTE chemistry applied to organic reactivity - mechanism, and physical organic principles - with a track record of results that changed experimental decisions
  • Demonstrated expertise applying machine learning to chemical data, including reaction outcome, reaction condition, or molecular property prediction
  • Demonstrated experience leading, managing, and developing scientists across multiple career stages
  • Track record of owning a scientific capability or platform end to end: setting direction, deploying it to real users, and iterating based on adoption and impact


Additional Skills / Preferences
  • Strong record of scientific contribution including peer-reviewed publications, presentations, and/or patents
  • Experience integrating foundation models or agentic systems into scientific workflows, including autonomous or semi-autonomous experimentation
  • Experience with automated and cloud laboratories, HTE platforms, and closed-loop optimization at scale
  • Depth in catalysis - metal-mediated, organocatalytic, or photoredox - and in catalyst and ligand design
  • Experience establishing evaluation and benchmarking methodology for models or agents, including safety review and failure-mode analysis
  • Experience with Bayesian optimization, active learning, or LLM-guided optimization for reaction conditions
  • Experience building and leading a scientific function or group from an early stage
  • Experience managing academic collaborations, consortia, or external technology partnerships
  • Experience contributing to scientific standards, governance, or advisory bodies for AI in science
  • Familiarity with medicinal chemistry principles and an understanding of scale-up considerations.
  • Proficiency with scientific and informatics tools such as ChemDraw, SciFinder, Reaxys, electronic lab notebooks, and data visualization platforms.
  • Examples of championing new technology adoption within a team or organization.
  • Strong work ethic with proactive, independent initiative; anticipates challenges and proposes solutions.
  • Highly organized with strong time management skills; adapts to changing business needs and timelines to deliver timely results.
  • Builds positive, respectful working relationships across teams, and engages in constructive dialogue even when navigating differing viewpoints.
  • Communicates clearly, thoughtfully, and professionally, adapting style to diverse audiences; actively listens and seeks to understand before responding.
  • Views personal success in the context of team success.
  • Proven ability to work effectively in a multidisciplinary, multi-site, international team environment


Additional Information

Travel: 0-15%. This is a primarily computational, lab-adjacent role with scientific leadership scope. You will work alongside laboratory teams and may spend time in research laboratory spaces to observe and direct experimental workstreams; standard personal protective equipment is required in those settings. The majority of the work is performed in an office and computing environment.

This job description is intended to provide a general overview of the job requirements at the time it was prepared. Job requirements may change over time and may include additional responsibilities not specifically described in the job description. Consult with your supervisor regarding

About Eli Lilly

ICOS Corporation is a biotechnology company that engages in the discovery, development, and commercialization of therapeutic products. It is engaged in the commercialization of treatments for unmet medical conditions, such as benign prostatic hyperplasia, hypertension, pulmonary arterial hypertension, cancer, and inflammatory diseases. It is the developer of a treatment known as Cialis (tadalafil), a product for the treatment of erectile dysfunction through its joint venture with Eli Lilly and Company in North America and Europe. It is also engaged in contract manufacturing services for third parties. It is in a strategic alliance with Solvay Pharmaceuticals, Inc. ICOS Corporation was established in 1989, based in Bothell, Washington. It is currently operated by Eli Lilly and Company.

Eli Lilly Careers

Joining Eli Lilly offers an unparalleled opportunity to become part of a leading global team dedicated to creating a healthier future. As a company revered for its commitment to innovation and leadership in the pharmaceutical industry, Eli Lilly is where your professional journey can flourish. Work You’ll Do At Eli Lilly, we are passionate about transforming patient care and advancing medical innovation. Our team at Eli Lilly is at the forefront of developing groundbreaking solutions in healthcare. By joining us, you will collaborate with some of the brightest minds in the industry, using cutting-edge technology to make real-world impacts. Lead with Innovation and Leadership Eli Lilly stands out in the marketplace by integrating deep industry expertise with robust research and development efforts. We are looking for professionals who are eager to drive change and lead the way in developing therapeutic breakthroughs. Explore Job Opportunities and Growth Eli Lilly offers a variety of career paths, including full-time positions and internships, across multiple functions such as research, marketing, IT, and sales. Whether you are a seasoned professional or a recent graduate, Eli Lilly provides an environment that promotes career growth and learning opportunities. Our commitment to diversity and leadership training ensures that every employee can achieve their potential. Be Part of Our Team Our team at Eli Lilly is committed to excellence and driven by a mission to improve lives. Employees enjoy a supportive culture that values collaboration, creativity, and diversity. We believe that a diverse workforce fosters innovation and helps us better connect with the communities we serve. Benefits and Culture Eli Lilly is dedicated to supporting our employees, offering competitive benefits, wellness programs, and comprehensive health care. Our culture is built on a foundation of respect, integrity, and quality, making Eli Lilly not just a great place to work, but a community to grow with. Networking and Professional Development Eli Lilly encourages continuous professional development and networking. With access to various training programs and mentorship opportunities, employees can enhance their skills and advance their careers. Our leadership is committed to nurturing talent through effective training and development strategies. Join Our Team Discover the exciting job opportunities at Eli Lilly by exploring open positions that match your skills and interests. We are continuously hiring and looking for individuals who are passionate, innovative, and ready to contribute to our mission of making life better for people around the globe. Stay Connected Keep up to date with the latest at Eli Lilly by following our careers blog. Gain insights from industry leaders and get tips on everything from crafting the perfect resume to preparing for your interview. Eli Lilly is not just a company—it's a place where you can make a difference. Explore the positions available and find out how your talents can help change the world. SEARCH ELI LILLY JOBS Stay ahead in your career with Eli Lilly, where innovation, leadership, and a commitment to diversity and growth lead the way to future advancements.
Learn more about Eli Lilly
Size
35,000 employees
Market Cap
$344.2 billion
Industry
Pharmaceuticals & Biotech
Net Income
$6.1 billion
Founded
1876
5 Year Trend
+5.9%
Revenue
$24.5 billion
NASDAQ
LLY
* Ladders Estimates

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