Data Scientist, RWE Clinical Trials - Remote Opportunity

Key Skills

Alteryx, Business Intelligence, Java Programming, PowerBI, Python Programming, R Programming, SAS, Spotfire, SQL, Tableau

Job Description

The Data Scientist – RWE will be responsible for generating Real-World Evidence (RWE) through advanced analytics and innovative approaches in the clinical trials space. The data scientist will be integral part of the Scientific Affairs team The candidate should have a strong desire to influence internal and external decision making through the application of innovative data science and technology. In this role, you will conduct sophisticated data analysis to help address critical business questions. This role reports to the VP of Scientific Affairs.

Job Responsibilities:

• Assists in the due diligence on new real world data providers/vendors and drive RWD quality assessments to inform investment decisions
• Works to mine raw data sets to deliver standardized, analysis-ready patient cohorts from in house data assets or online licensed platforms, including generating hypotheses and analyzing data to test and interpret results standardized in close collaboration with the value and outcomes research and patient/market access team and help shape the analytics strategy
• Partners with other members of the Walgreens Clinical Trial team members to deliver actionable insights from real-world, clinical and other data sources to support biopharmaceutical RWE and clinical trial requests. Potential efforts include analysis of unmet needs (safe and effective therapy in certain disease states), treatment patterns and healthcare/economic burden data to support budget impact modelling and cost effectiveness modeling
• Cleans, transforms and stores data into an integrated data lake for future analysis and broader team consumption
• Performs data mining and statistical analysis to analyze RWE/RWD in order to find new insights regarding patient populations and treatment outcomes
• Supports the development of real-world data, analytics and platform capabilities, applying cutting-edge advanced analytics methodologies and tools to address scientific questions from biopharmaceutical companies
• Collaborates on design and execution of outcomes research studies from a data science and analytics perspective
• Ensures high quality, rigorous and readily interpretable deliverables from RWE studies/analyses
• Builds dashboards, analytics and reports for internal and external consumption.

Basic Qualifications

• Bachelor’s Degree and at least 4 years of experience in quantitative or computational functions OR High School/GED and at least 7 years of experience in quantitative or computational functions
• Analytics experience in R, Python, SQL.
• Experience in designing and executing robust and reproducible statistical analyses in the context of epidemiology and observational research with healthcare data
• Knowledge of common statistical testing techniques including hypothesis testing, ANOVA/ANCOVA/MANOVA, generalized regression models, and common machine learning techniques
• Experience processing large data from various data sources
• Experience handling of protected patient health information
• Knowledge of at least one of the following: Tableau, Power Bi, Alteryx, Spotfire, Metabase or other BI intelligence tools
• At least 2 years of experience contributing to financial decisions in the workplace.
• At least 2 years of direct leadership, indirect leadership and/or cross-functional team leadership.
• Willing to travel up to 10% of the time for business purposes (within state and out of state).

Preferred Qualifications

• PhD, Master’s degree in, statistics/biostatistics, computer science, mathematics, systems engineering, biomedical engineering or related field
• Familiarity with SAS
• Expertise in EMR/Health IT, disease registries, and insurance claims databases
• Expertise in clinical data standards, medical terminologies and controlled vocabularies used in healthcare data and ontologies (ICD9/10/ReadCode)
• Experience in Good Clinical Practice (GCP) and/or regulatory compliance guidelines for real-world evidence studies or clinical trials (e.g., ISO, MDD/MDR, CFR)
• Experience working on alternative data sources and alternative methods of clinical data collection, especially those enabled by technology platforms and/or solutions.
• Experience with adaptive designs, Bayesian modeling, sequential data, and computational statistics
• Understanding of statistics and machine learning methods, ability to continue self-learning of technical and non-technical skills