Data Scientist - RWE - United States - Remote

Overview

Luminary Group is partnering with a leading life science company in their search for a talented and experienced Data Scientist with expertise in Real-World Evidence (RWE). As a Data Scientist, you will play a crucial role in analyzing and interpreting real-world data to generate valuable insights and support evidence-based decision making in the healthcare industry.

In Short

• Identify and define analytical problems related to real-world evidence (RWE) and develop appropriate data-driven solutions.
• Design and implement data mining and statistical modeling techniques to analyze complex RWE datasets.
• Preprocess and clean large-scale real-world data to ensure quality and integrity.
• Apply machine learning algorithms and techniques to extract meaningful patterns and insights.
• Develop predictive models to forecast outcomes and trends based on real-world data.
• Collaborate with cross-functional teams to interpret and communicate analysis findings to stakeholders.
• Stay up-to-date with the latest research and advancements in data science and real-world evidence.
• Implement data visualization techniques to effectively communicate analysis results.
• Participate in the development of data-driven products and solutions for the healthcare industry.

Requirements

• Proven experience as a Data Scientist or similar role.
• Strong knowledge of statistical modeling and data mining techniques.
• Experience with machine learning algorithms and predictive modeling.
• Proficiency in programming languages such as Python or R.
• Familiarity with data visualization tools.
• Excellent analytical and problem-solving skills.
• Ability to work collaboratively in a team environment.
• Strong communication skills to present findings to stakeholders.
• Background in life sciences or healthcare is a plus.

Benefits

• Competitive salary and benefits package.
• Opportunity to work on impactful projects in the healthcare industry.
• Flexible working hours and remote work options.
• Professional development and training opportunities.
• Collaborative and innovative work environment.