Job Description:
We are seeking an agile, creative, and highly self-motivated data scientist to integrate genetic, phenotypic, and molecular profiling data for the discovery and development of new therapeutics. The successful candidate will work at the cutting edge of science and drug discovery to solve important scientific challenges in drug discovery. S/he will work in a highly interdisciplinary environment along-side experimental biologists to interpret results of large-scale data analysis in the context of smaller-scale “bench” experiments and project strategy. The position involves integrating high quality internal and external data across species and data-types to identify new drug targets and biomarkers, progress discovery projects, and identify patient stratification strategies. The position will require the successful candidate to provide high quality solutions to enable rapidly evolving project demands. S/he will balance nimble analysis approaches for exploratory innovative projects/technologies with documented and reproducible analysis of clinical data. S/he will have the opportunity to work in an exciting, collaborative environment, constantly learning new skills and scientific knowledge while simultaneously advancing science for meeting unmet medical need. Minimum requirements: The successful candidate will have a strong scientific background with computational training, such as a PhD or Masters degree in bio/cheminformatics, computational biology/chemistry, genetics, biology or related field. Required attributes include: • Hand-on experience with GWAS analysis and integrating genetic/phenotypic data with molecular profiling data. Strong knowledge of public genetic and phenotypic data sources. • Excellent scripting skills (ideally Python, R) • Hands-on experience applying standard statistical approaches to large scale data • Relevant work experience using scientific computing in a life-science environment • Excellent interpersonal and communications skills • Ability to learn, apply, and assess novel analysis techniques with a results-oriented approach • Demonstrated problem-solving and organizational skills • Ability to work independently as well as on a team • Excellent written and oral English; any additional language a plus Desirable skills include, but are not limited to: • Hands-on experience with multivariate, single cell data visualization and analysis • Hands-on experience with Machine Learning algorithms, pattern recognition approaches • Wet lab experience • Experience working with databases
Additional Info:
EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers and take pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.[Click Here to Access the Original Job Post]
We are seeking an agile, creative, and highly self-motivated data scientist to integrate genetic, phenotypic, and molecular profiling data for the discovery and development of new therapeutics. The successful candidate will work at the cutting edge of science and drug discovery to solve important scientific challenges in drug discovery. S/he will work in a highly interdisciplinary environment along-side experimental biologists to interpret results of large-scale data analysis in the context of smaller-scale “bench” experiments and project strategy. The position involves integrating high quality internal and external data across species and data-types to identify new drug targets and biomarkers, progress discovery projects, and identify patient stratification strategies. The position will require the successful candidate to provide high quality solutions to enable rapidly evolving project demands. S/he will balance nimble analysis approaches for exploratory innovative projects/technologies with documented and reproducible analysis of clinical data. S/he will have the opportunity to work in an exciting, collaborative environment, constantly learning new skills and scientific knowledge while simultaneously advancing science for meeting unmet medical need. Minimum requirements: The successful candidate will have a strong scientific background with computational training, such as a PhD or Masters degree in bio/cheminformatics, computational biology/chemistry, genetics, biology or related field. Required attributes include: • Hand-on experience with GWAS analysis and integrating genetic/phenotypic data with molecular profiling data. Strong knowledge of public genetic and phenotypic data sources. • Excellent scripting skills (ideally Python, R) • Hands-on experience applying standard statistical approaches to large scale data • Relevant work experience using scientific computing in a life-science environment • Excellent interpersonal and communications skills • Ability to learn, apply, and assess novel analysis techniques with a results-oriented approach • Demonstrated problem-solving and organizational skills • Ability to work independently as well as on a team • Excellent written and oral English; any additional language a plus Desirable skills include, but are not limited to: • Hands-on experience with multivariate, single cell data visualization and analysis • Hands-on experience with Machine Learning algorithms, pattern recognition approaches • Wet lab experience • Experience working with databases
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Additional Info:
EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers and take pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.[Click Here to Access the Original Job Post]