Job summary:
The digitization and availability of the vast amount of real world patient data has created significant opportunity to understand real world patients and their clinical experiences, beyond traditional research in standard clinical trials. The increasingly affordable genomic sequencing technologies also made it possible to study and treat patients based on their genetic make-up. You will join our Data Science team at Roche Innovation Center New York to mine the rich and highly curated electronic healthcare records (EHR) integrated with genetics data in our Flatiron-FMI data marts, as well as public data sources where appropriate. By applying advanced analytics, you will generate evidence from real world data that can increase our understanding of disease biology, drug resistance and/or drug response mechanisms, hence help accelerate our drug development and bring new medicine to patients. In this position, you will have the rare opportunity to apply your analytical skills in statistics, machine learning, deep learning and biological pathway analysis to cancer immunotherapy challenges, using valuable integrated patient data.
Responsibilities:
Identify and apply appropriate analytical methods to ensure fit-for-purpose approaches.
Apply rigor in study design and analysis plan. * * Prepare data and perform data analysis.
Interpret results, create visualization and generate reports to convey new insights in cancer biology in a way that maximize impact and interpretability.
Present work internally and at conferences.
Publish in peer-reviewed journals.
Requirements:
Ph.D. in biology- or data-related sciences such as Molecular Biology, Biomedicine, Computational Biology, Bioinformatics, Data Science.
Knowledge and experience in cancer immunology is a must. Additional knowledge and experience in epidemiology is a plus.
Strong quantitative analytical skills in statistics, machine learning and predictive modeling.
Proficient in an**alysis programming skills (e.g. R or Python) and SQL.
Experience in analysis of Real World Data such as EHR and health insurance claims is highly desired.
Experience in analysis of large scale genetic data is also highly desired.
A creative self-motivated individual with excellent communication skills.
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