Research Scientist-Computational Biology/Bioinformatics
At Lilly, we have a history of addressing the needs of individuals living with Diabetes by providing breakthrough therapies that result in meaningful improvements in patients’ lives. We continue to build on this history through research and development efforts that aim at next generation therapies. We have one of the largest pipelines in Diabetes in the industry and are committed to continuing to build our leadership in Diabetes and its complications through innovation in drug discovery and development. Lilly strives to employ passionate, innovative researchers who are dedicated to the science as well as our community and the world in which we live.
The Diabetes and Complications Therapeutic Area is seeking a highly motivated Research Scientist to join a team that is discovering first- and best-in-class medications. This team uses quantitative approaches that leverage large, disparate data types to better understand underlying biology of disease and how patients respond to treatment. Are you able to foster intellectual sharpness and creativity in this role, offering unique insight into how to best utilize genetic, genomic, chemical, clinical, and real world evidence in drug discovery? We are looking for someone like you to be a part of our interdisciplinary and collaborative team working to make life better for patients worldwide. Are you energetic and passionate about the future of drug development and improving patient's lives? Do you have a desire to take Lilly bioinformatics and computational biology capabilities to the next level in order to drive medicines to patients faster?
You will have the opportunity to contribute to Teams with Diabetes and Complications Translational Scientists, Chemists, Physicians, Information Technologists, Statisticians, and fellow Computational Biologists that:
- Integrate public data, drug discovery information, knowledge obtained from clinical trials, and real-world evidence to identify drug targets, assess target risk, and generate novel disease insight.
- Answer key questions for advancing the Diabetes and Complications R&D asset portfolio projects, where deep scientific understanding is needed to circumvent drug development issues.
- Develop new research methods using clinical and real world data offerings to advance our knowledge of medicines and how they work in patients
- Own the evaluation, selection, and acquisition of complex external data and partnerships for retrospective research
- Deliver insights to researchers through statistical analysis of genotype/phenotype association data
- Develop innovative analytic methods and regularly communicate with business partners through various presentation media. Engage and collaborate with internal and external authorities to assure best practices and key capabilities in bioinformatics.
- Engage key Diabetes and Complications R&D partners organizing value-focused research projects.
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 39,000 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.
- PhD in statistical genetics, bioinformatics, mathematics, statistics, computer or biological disciplines,
- Diverse experience applying analytics, modeling and statistics in complex data analysis environment preferred.
Lilly is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status
- Deep knowledge of mathematics and statistical methods and mathematical competency using statistical analysis software or libraries such as R or Matlab.
- Proficiency with one or more general scripting languages such as Python, Perl, or Ruby, and data visualization tools (Spotfire, R, Python).
- Comfortable with Unix/Linux, SGE clusters, shell scripting.
- Knowledge and hands-on experience of major public and commercial information databases
- Fluency with major public genomics/genetics initiatives and databases such as GEO, ENCODE, GTEx, ExAc etc.
- Exposure to real world healthcare data, pharmaceutical industry research information, and clinical research data (biomarkers, omics data) preferred.
- Experience handling data-driven research from project inception to client communication.
- Proven capabilities in partner engagement and matrix team leadership.
- Proven strong writing and oral presentation skills.