Derive insights from Clinical Data using Advanced Analytics

Project Description

Work as part of a team of consultants helping a large Pharmaceutical company to derive insights on accelerating Patient Recruitment from clinical data and other data sources. Experts living in New Jersey (within driving distance to our office in Warren, NJ) will be given preference, but candidates outside of this area will still be considered.

Responsibilities:

• Transform real-world clinical data into actionable insights using data science, robust statistical methods and compelling data visualizations
• Define and clarify analytic requirements, develop analysis plans, ensure data quality standards, and create publication-ready methods and results
• Work with cross-functional team to understand and clarify analytic requirements and identify areas for automation and process efficiencies

Requirements:

• You hold a Master’s degree or PhD in a quantitative discipline, such as biostatistics, epidemiology, applied statistics, or health economics
• You have at least 3-5 years of relevant work experience analyzing clinical data
• You love working with data and have experience exploring data with a critical and thoughtful eye
• You excel at a statistical programming language (we primarily use R, but are open to people with experience in any language)
• You are a brilliant communicator, both oral and written
• You are self-motivated, thrive in highly uncertain situations, and enjoy coming up with elegant and innovative solutions to challenging problems
• You are a “do-er” - you know how to balance attention to detail with quick execution against tight timelines
• You are flexible and adapt well to complex challenges
• You are passionate about our mission to improve healthcare through technology
• You are a highly-effective collaborator and are motivated by the opportunity to work with oncologists, software engineers, product managers, and other members of the team

Prefered, but not Required:

• Oncology experience
• Consulting experience
• Experience working with longitudinal EMR data