BACKGROUND:
The Company is an early stage company addressing the emerging opportunities in personalized medicine. The Company’s strategic vision is to create and dominate a molecular cytology market to improve the early diagnosis and staging of cancer. The Company has extensive biomarker discovery efforts underway and has licensing and joint collaboration projects in process with leading academic institutions. The company has spent the last year validating its business model with key stakeholders: physicians, patients and payers, has recently closed a significant round of private equity financing with premier venture capital investors, and is now positioned for rapid expansion and execution of its business plan. This is an exciting time to become part of this dynamic business team.

RESPONSIBILITIES:
The Director of Biostatistics will be become an important member of our founding team at our headquarters in South San Francisco, reporting to the SVP of Research and Development. S/he will have primary responsibility for the “hands on” comprehensive analysis of complex genomic datasets, applying knowledge of classification methods to generate gene signatures for disease prediction. The ideal candidate will have the opportunity to develop new methodology in this rapidly evolving field. S/he will ultimately be responsible for developing software suites for applications in genomics, using the Company’s proprietary algorithms. This position leads the creation and advancement of algorithms in bioinformatics and computational biology with a product development focus involving the use of techniques from applied mathematics, informatics, statistics, computer science, artificial intelligence, gene expression and DNA polymorphism analysis. S/he will initially have management responsibility for one or more direct reports.

Specific Responsibilities:

• Extract, manipulate, transform, and analyze large, diverse RNA and DNA data sets emanating from the cancer gene discovery and clinical validation efforts
• Utilize understanding and experience in assessing data quality and data normalization for gene expression and DNA polymorphism data
• Apply skills in advanced mathematics, logic, and statistics to translate these concepts to algorithm development
• Evaluate data collected as part of ongoing clinical trials as well as mining of data submitted to and available from the FDA
• Structure clinical trials, specifically in powering sample sets to an adequate level to achieve statistically significant robust biomarkers
• Create statistical analysis plans
• Create statistical text for study concept documents and protocols (study design, endpoints, sample size, methods for analysis)
• Develop and maintain standardized statistical approaches and methodology
• Utilize independent project management skills to ensure timely and reliable results
• Manage and direct the work of one or more junior employees to achieve timely project deliverables

REQUIREMENTS:

• PhD in Statistics/Biostatistics/Mathematics with an emphasis on biologically related systems.
• Minimum of (7) years experience in the field with a proven successful track record in analysis of highly complex and large genomic datasets and algorithm development
• Track record of managing 1 or more employees as well as a demonstrated record of project management success
• Experience with statistical modeling including some or all of the following: linear and non-linear programming, linear regression analysis, parametric and non-parametric techniques, principal components analysis and ANOVA etc.
• Experience with mathematical modeling and a variety of software packages
• Broad and deep knowledge of software and hardware platforms, software development/ programming languages, commercially leading database management systems, storage technologies and data communications and software development life-cycles (SDLC).
• Experience with the following Operating Systems: Windows, UNIX, LINUX and Databases: Oracle/SQL/mySQL strongly preferred
• Demonstrated experience in software engineering
• Critical understanding of genomics/ oncology data and system biology including gene expression profiling, human DNA variation, proteomics and/or pathway analysis, together with the understanding of biological variability, technical variability, and method variability inherent in microarray and genomic data.
• Experience in biomarker discovery and selection using gene expression or DNA polymorphism data a plus
• Working knowledge of a variety of data visualization software programs and hands-on experience with a variety of web technologies/packages strongly preferred
• Experience and ability to manage outside consultants.

HOW TO APPLY:
Please submit resumes to:
SRA-San Francisco
Steve Merwin
swm[at]srasf.com