Epidemiology Director, Project Data Sciences – Cardiovascular & Retina



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Key Responsibilities:

·     The Project Data Scientist makes significant and creative contributions to a research or creative project in his/her academic discipline.

·     Provides medical and scientific contribution to a matrixed cross-functional Compound Development Team and Clinical Team

·     Participate on and may lead cross-functional teams for evaluation of new scientific opportunities, disease areas, product ideas, implement franchise business strategies, etc. 

·     The Project Data Scientist will work in collaboration with leadership to create, execute and align the data science strategy with the overall Disease Area Stronghold (DAS) strategy

·     He/She will design specific projects, including the selection of appropriate methods and techniques. In some cases, may monitor trouble-shooting problems, interpret results, and plan follow-up experiments

·     Authors abstracts and manuscripts for publication based on clinical trial data


·     MD, PHD, or PharmD (or equivalent) in relevant area with appropriate post-doctoral training and certification

o  MD (or equivalent) is preferred. Board certification in cardiology, diabetes, endocrinology and metabolism, or nephrology is preferred

·     PHD, MPH or equivalent experience in Real World Evidence (RWE) Data Science is preferred. A strong background in RWE/Data Science, as evidenced by an advanced degree in statistics, bioinformatics, computational biology, epidemiology, applied mathematics, computer science, physics, engineering or related fields

o  Specific discipline preferred: Retina OR Cardiovascular/Anti-Coagulation. Experience working in pharmaceutical industry with strong knowledge of drug development is preferred.

·     6-8 years of work experience within a clinical/laboratory setting, as well as operational functions

·     Can effectively apply a Data Science lens to clinical functions

·     Excellent written and verbal communication skills

·     Experience working in a matrix/cross-functional clinical environment


Required Technical Knowledge and Skills:

·     Experience handling healthcare relevant datasets (HER, registry data, etc.)

·     Strong working knowledge of machine learning algorithms (Random Forest, SVM, neural networks, etc.), exploratory data analysis, statistical modeling, signal processing and/or Natural Language Processing techniques is required

·     Experience with large datasets, understanding of data analysis workflows, software engineering (databases, cloud computing) and/or querying languages such as SQL

·     Proficiency with one or more programming language such as Python, R, C++, or Java is required


Principal Relationships:

·     Data Sciences

·     Epidemiology

·     Quantitative Sciences

·     Compound Development Teams

·     Discovery

·     Biomarkers

·     Late Development

·     Staff from departments of Business Development, Global Commercial Strategy Organizations, etc

Medasource provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.