Location:  Indianapolis, IN

Ideal Candidate:

7+ to 10 years of experience
Management Experience Required – No
Minimum Education – Doctoral

This is a technical leadership position within the Protein Optimization Team of Biotechnology Discovery Research with responsibility for identification and evaluation of therapeutic lead molecules, material generation, characterization, and optimization of biotherapeutics as projects progress from target identification to lead optimization and development. In addition to providing technical leadership for projects, the individual will supervise scientists with BS, MS and/or Ph.D. degrees, propose strategies and future directions to meet project and departmental goals, and effectively communicate progress to management and governance committees. This candidate will interact cross-functionally within Biotechnology Discovery Research and Applied Molecular Evolution, as well as the Drug Hunting Teams in different therapeutic areas, Drug Disposition, Regulatory and Bioproduct Development, as projects move from the bench/concept to the clinic.

KEY OBJECTIVES/DELIVERABLES:

Lead reseach efforts that support project teams from concept through Lead Optimization with responsibility for identification of lead therapeutic molecules, material generation and characterization of biopharmaceutical properties using biochemical and biophysical techniques, and implementing molecular engineering strategies to improve drug properties of therapeutic antibodies and proteins. This requires a broad repertoire of skills and knowledge including protein expression, protein purification, physicochemical characterization, as well as a strong understanding of protein engineering concepts.

Drug Hunting Focus: The candidate is expected to exhibit strong problem solving abilities and be familiar with understanding and resolving issues ranging from biology to bioproduct developability. Prior experience with the strategies employed in moving a therapeutic opportunity from a cellular or molecular concept to proof of principle confirmation in humans is seen as an advantage.

Leadership: In advancing the optimization of lead therapeutic molecules, the candidate will be required to lead/co-lead multidisciplinary teams. Accordingly, strong communication and presentation skills in sharing research findings and team plans, and effective team work will be required

MINIMUM REQUIREMENTS:

A Ph.D. degree in the biological or chemical sciences

8 to 12 years of experience in a biotechnology or pharmaceutical company with a demonstrated leadership in protein structure function analyses and protein engineering and a track record of advancing biotherapeutics, e.g. therapeutic proteins or antibodies from concept to clinical development.

5-8 years of supervisory experience in directing other scientists, including Ph.D. level senior scientists, in the design and execution of experiments is required

Deep expertise of protein structure and post-translational modifications, and experience using state of the art analytical methods to characterize proteins, as demonstrated by publications or patents.

ADDITIONAL PREFERENCES:

Strong communication and presentation skills, in sharing research findings and team plans, and effective team work will be required.

Appreciation of protein formulation requirements and experience incorporating pharmaceutical developability assessment in protein optimization and candidate identification.

Understanding of the global regulatory requirements to advance biotherapeutics through clinical development.

Demonstrated ability to work cross-functionally, and excellent organizational, communication and presentation skills.

Location: Indiana 

10+ to 15 years of experience
Management Experience Required – No
Minimum Education – Doctoral

Willingness to Travel – Occasionally

The Data Mining group within Advanced Analytics focuses on developing new models, algorithms, and tools in a wide range of technical and business areas, including many areas of Research & Development, healthcare data from electronic medical records or claims databases, Sales & Marketing, Customer Service/Response, B2B, and more.  This opening is for an experienced researcher in applied mathematics, statistics, informatics or other areas of science with an emphasis on data mining and analysis of data. We are especially interested in persons with expertise in developing models based on findings from data mining efforts and understanding variability and spurious/biased findings (i.e. statistical validity) that may come from data mining projects. Successful candidates are expected to work with multidisciplinary teams to solve challenging problems of importance to drug research, development and commercialization. They will also conduct innovative research, publish and present results in refereed journals and conferences.

The successful candidate will provide statistical/mathematical data mining support in multiple dimensions including:

-                  provides technical leadership and expertise to execute multi-disciplinary or cross functional projects that will influence the Lilly Research Laboratory and the Statistical Science organization;

-                  leads the assessment and introduction of new statistical/mathematical technology and methodology to apply to broader practice;

-                  provides consulting on priority R&D/business projects to define questions/problems of interest, define necessary data sources, and effectively communicate findings to scientific and business partners.

-                  assist with decision-making by effective data mining project plans across Eli Lilly

-                  provide appropriate technical oversight and coaching of a small staff of PhD data mining scientists and statistical programmers.

-                  Work with drug/compound Research Teams and a broad variety of business functions to apply data mining techniques to assist in analysis and decision-making.

-                  Perform research and develop methodologies, especially in data mining and other innovative statistical/mathematical approaches.

-                  Stay current with respect to statistical/mathematical/informatics modeling methodology, to maintain proficiency in applying new and varied methods, and to be competent in justifying methods selected.

-                  Develop approaches or solutions that save time, increase efficiency, facilitate decision-making or otherwise directly impact our drug research or business objectives.

-                  Collaborate with other scientists and drug/compound Team personnel to provide input on study protocol and study design through the use of data mining on past studies or other data sources.

-                  Participate in peer-review work products from other statistical/analytical colleagues, and advise others on technical matters.

-                  Can effectively lead cross-functional or multi-disciplinary groups and use technical expertise to influence business decisions through statistical/mathematical analysis and interpretation.

-                  Collaborate with team/functional colleagues to write reports and communicate results.

-                  Assist with, or be responsible for, communicating study results via manuscripts, or oral presentations in group settings, as well as for communicating one-on-one with key customers and presenting at scientific meetings.

-                  Assist project statisticians in responding to regulatory queries and to interact with regulators as needed.

-                  Have broad understanding about the drug development business to assist in defining data mining projects that may improve efficiency in our business.

-                  Understand disease states in order to enhance the level of customer interaction and collaboration and be seen as a strong scientific contributor.

-                  Perform work in full compliance with assigned curriculum(s) and will be responsible for following applicable corporate, medical, local, and departmental policies, procedures, processes, and training.

-                  Develop, train, educate others in Statistical Sciences and other technical disciplines in research and business on the use of data mining methods and tools.

If interested, please submit your resume to resumes@acquis.com.  Thank you!