Scientist, Data Scientist

Listing Info We are seeking an exceptional individual to join our Data Science team at the Roche Innovation Center New York. The Data Scientist will employ a combination of analytical, informatics and computational skills and scientific domain knowledge to provide timely analytic solutions for data-driven decision making in drug project teams. The candidate will work closely with translational scientists and collaborate with other data experts and business stakeholders to contribute directly clinical and translational project to bring innovative medicines to patients. This role requires strong technical and scientific knowledge combined with an excellent capacity to communicate and lead in a multi-disciplinary environment. The candidate will be a self-motivated and focused individual who brings new ideas, energy and agility to the team that is passionate about serving customers and creating measureable scientific and business impact. Responsibilities

• Partner with clinical research scientists and other data experts to identify and address data analysis needs in project teams
• Identify relevant data sources and apply a variety of tools and techniques to prepare and manipulate the data for analysis, develop algorithms and predictive models, perform data analysis, create visualization and reports, and present findings and recommendations.
• Mine massive amounts of public and in-house genomic data and extract useful insights. Explore and identify analytics opportunities by collecting new data or mining existing data, with a thorough understanding of the scientific and business context of these analytics techniques
• Lead or contribute to informatics/analytics projects requiring deployment of analytics models in a larger technology platform
• Contribute to the overall team effectiveness by creating and disseminating new analytics framework, methodology and practices.

• This position requires a Ph.D. in data-related sciences such as Computational Biology, Bioinformatics, Statistics, Applied Mathematics, Computer Science, and Physics.
• Strong analytical skills in machine learning, statistical analysis, predictive modeling, text analytics (e.g., NLP).
• Experience in analysis of large scale genomic data such as whole genome/exome sequencing, RNA-seq, CNV, microarray gene expression. Broad knowledge and experience with public genome databases (e.g., TCGA) and open-source genomic analysis tools.
• Ability to develop scientific software in one or more of programming languages, e.g., Java, Python, R, Perl, SQL, and C/C++.