Pfizer Bioinformatics Job Posting Desc

ROLE SUMMARY

Pfizer is making significant investment in the creation of novel, first-in-class therapeutics, by combining internal discovery and validation of drug targets with external partnerships to produce clinical drug candidates for the Pfizer pipeline.  This position will work within the Target Sciences (TS) group, which has collective expertise in human genetics and functional genomics, computational biology and data management, and target validation biology, and an overall remit to discover and validate hypotheses for novel, emerging science drug targets.  The primary responsibility of this position is to design, develop, execute and interpret computational experiments, utilizing relevant internal and external biological data sources, to advance drug-discovery targets within Pfizer’s Centers for Therapeutic Innovation (CTI) and emerging science target hypotheses emanating from TS internal efforts and from Pfizer’s industrial-academic partnerships.  To this end, the position will be responsible for the development of bespoke analytical and visualization tools, supporting pipelines and workflows, and data integration environments; and will work closely with the emerging science geneticists, biologists and functional genomics scientists in TS and with CTI project leads. This position requires a deep expertise in bioinformatics, including computational workflows and pipelines, tools and methodologies, and data integration techniques.  The position will benefit from additional expertise in computational biology, incl. some knowledge of disease pathophysiology in at least one disease area of interest to Pfizer R&D; some experience in progressing target hypotheses and projects through computational approaches and insights in a pharmaceutical Research setting; and an ability to achieve impact through focus within a wide swath of potential project and technology opportunities.

ROLE RESPONSIBILITIES

Engage with TS and CTI project teams to advance critical target validation objectives through the development and application of computational approaches, and to champion innovative proposals that extend such approaches.
Develop and apply bespoke computational algorithms and workflows to support project-specific analytical and visualization tasks required for decision making in Emerging Science projects.
Deliver computational analyses of high-dimensional datasets, e.g., RNA-Seq, NGS, proteomics or metabolomics, from model systems, disease systems, and molecular profiling databases to understand the interplay between disease biology, genes and mechanisms that enable progression of emerging science target hypotheses and discovery projects.
Integrate multiple levels of biological information to inform protein-disease networks in the context of emerging science drug discovery.
Provide hypotheses and insights based on complex, multi-dimensional data analyses to inform and aid in design of biological validation studies to be conducted by the Emerging Science genomics and biology groups, CTI project teams and/or RU project teams for functional validation (e.g., siRNA, CRISPR/Cas9) of emerging science target hypotheses and projects.
In partnership with RU computational biologists, the Computational Biology platform group, and non-clinical biostatistics, identify novel data sources, computational methods, and external collaborations that will grow capabilities in computational target validation.
Support key internal/external collaborations that secure access to innovative computational methodologies and/or relevant datasets to advance our ability to understand disease pathophysiology from large-scale molecular and phenotypic data.
BASIC QUALIFICATIONS

Ph.D. in Computational Biology, Biological Sciences, Bioinformatics, Computer Science, Applied Mathematics or other natural science required; 2+ years relevant experience applying quantitative approaches to solving biological problems, preferably in a pharmaceutical, biotech or comparable context.
Background in human biology/medicine, with some knowledge of disease pathophysiology in at least one disease area of interest to Pfizer R&D, e.g., Immunology & Inflammation, Oncology, Rare Disease, and Internal Medicine.
Curiosity about biological and pathological processes and mechanisms.
Excellent technical proficiency in multiple programming, scripting, querying or statistical analysis languages, incl. R, Python, PERL and SQL.
Demonstrated experience in the design, development, execution and interpretation of data generation and computational experiments on in vivo and in vitro biological data, especially RNA-Seq or other NGS data.
Demonstrated experience in delivering insights and hypotheses from complex multi-dimensional biological data in a biomedical context.
Demonstrated experience in applying computational approaches to deliver insights and hypotheses, e.g., multi-variate, Bayesian and machine learning approaches.
Pharmaceutically relevant experience or formal training in computational biology, bioinformatics, computer science or medicine.
Demonstrated ability for sound experimental design of in-silico experimentation/workflows required, in addition to ability to effectively interface with Emerging Science / CTI biologists to communicate/discuss results, ideas, and follow-up experiments.
Working knowledge of relevant public and proprietary databases, methods and tools.
Excellent communication skills (oral and written) as demonstrated by publications and presentations.
NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS

Occasional travel will be required to non-Cambridge Pfizer sites and to scientific meetings.

EEO & Employment Eligibility

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status.  Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA.   Pfizer is an E-Verify employer.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure.  Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act.  Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government.  If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

Eligible for Relocation Package

Eligible for Employee Referral Bonus

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.