Senior Scientist II, Discovery Bioinformatics at Exelixis, Inc. in Alameda, California

Job Description:

SUMMARY/JOB PURPOSE:

We are seeking an innovative scientist to help build Exelixis' bioinformatic efforts in oncology drug discovery. The successful candidate will leverage multi-omic datasets along with techniques from data science, predictive modeling, and other cutting-edge bioinformatic methodologies, in order identify and characterize novel drug targets. In order to be successful in this endeavor, the role requires a self-starter who can initiate and operate data analysis environments on cloud platforms.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Use a data-driven approach to aid in drug-target identification, characterization, and validation
  
  


• Collaborate with cancer biologists, immunologists, chemists, statisticians, to develop computational strategies and build tools for patient stratification, and development of pharmacodynamic and predictive genomic signatures
  
  


• Communicate findings at internal and external meetings
  
  


• Direct work only (no direct reports, but directing work to a CMO, Consultant or 3rd party.)
  
  

SUPERVISORY RESPONSIBILITIES:

• None
  
  

EDUCATION/EXPERIENCE/KNOWLEDGE & SKILLS:

Education:

• Bachelor's degree in computational biology, engineering, statistics, cancer biology, immunology, genetics, or similar field and a minimum of 9 years of experience; or,

• Master's degree in computational biology, engineering, statistics, cancer biology, immunology, genetics, or similar field and a minimum of 7 years of experience; or,

• PhD degree in computational biology, engineering, statistics, cancer biology, immunology, genetics, or similar field and a minimum of 2 years of experience; or,

• Equivalent combination of education and experience

Experience:

• Experience in utilizing transcriptome-wide data to derive predictive and pharmacodynamic gene expression signatures from the pre-clinical and clinical multi-omic data. Experience within or collaborating with industry drug-development programs is a plus
  
  


• Extensive expertise in programming using languages such as R or Python and analysis of multi-dimensional genomic and/or proteomic datasets, particularly transcriptome-wide data from pre-clinical, and ideally, clinical samples
  
  


• Working knowledge of applied statistical/biostatistical methods such as proper application of distribution analysis, enrichment analysis, differential survival analysis, and significance testing.
  
  


• Experience deriving and validating predictive and prognostic gene expression signatures using transcriptome (RNA seq) data is required. Familiarity with both classic predictive modeling (e.g., SVM) as well as survival modeling (CoxPH) is a plus.
  
  


• Hands-on experience initiating and maintaining remote-based computing environments for data storage, access, and analysis such as AWS EC2 instances and S3 buckets.
  
  


• Strong capability with data visualization using R or Python as well as excellent data communication skills
  
  

KNOWLEDGE/SKILLS/ABILITIES:

• Strong track record of systematically evaluating and prioritizing multiple hypotheses using bioinformatic approaches both independently and collaboratively
  
  


• Excellent problem-solving and collaboration skills
  
  


• Strong communication, data presentation, and visualization skills
  
  


• Strong scientific expertise with robust track record of publications
  
  

WORKING CONDITIONS:

• Environment: primarily working in an office environment

#LI-BC1

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

DISCLAIMER
The preceding job description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

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