Experienced Data Scientist – Remote Part-Time Opportunity in Healthcare Data Analysis and Insights Generation

Introduction to arenaflex arenaflex is a leading organization in the healthcare industry, dedicated to improving patient outcomes and advancing medical research through innovative data analysis and insights generation. As a part of our team, you will have the opportunity to work with a talented group of professionals who share a passion for using data to drive meaningful change in the healthcare sector. Our organization is committed to fostering a culture of collaboration, innovation, and continuous learning, and we are excited to invite talented individuals to join our team as a Data Scientist. Job Summary In this part-time remote role, you will be responsible for creating Real-World Evidence (RWE) through advanced analysis and innovative methodologies in the clinical trials space. As a key member of the Scientific Affairs team, you will have the opportunity to impact internal and external decision-making through the use of cutting-edge data science and technology. Your primary focus will be on leading sophisticated data analysis to address critical business questions, and you will report to the Chief, Clinical Data Science. Key Responsibilities Mine raw data sets to deliver standardized, analysis-ready patient datasets from in-house data resources or licensed platforms, analyze and interpret results, and help shape analysis strategy. Collaborate with other members of the arenaflex Clinical Trials team to deliver meaningful insights from real-world, clinical, and other data sources to support biopharmaceutical RWE and clinical trial requests. Clean, transform, and store data into an integrated data lake for future analysis and broader team use. Perform data mining and statistical analysis to analyze RWE/RWD and discover new insights regarding patient populations and treatment outcomes. Support the development of real-world data, analytics, and platform capabilities, applying advanced analytics and tools to resolve scientific questions from biopharmaceutical companies. Collaborate on the design and implementation of outcomes research studies. Ensure high-quality, comprehensive, and readily interpretable predictions from RWE studies and analyses. Build dashboards, analysis, and reports for internal and external use. Conduct a thorough review of new real-world data suppliers and vendors and drive RWD quality assessments to inform project decisions. Essential Qualifications To be successful in this role, you will need to have: 2 years of experience with R, Python, or SQL. Experience in designing and executing effective and reproducible statistical analyses in the context of epidemiology and observational research with healthcare data. Knowledge of common statistical testing methods, including generalized linear models, clustering and classification, decision trees, solo learning, time series analysis, and survival analysis. Experience handling large data from multiple data sources. Experience handling protected patient health information. Knowledge of at least one of the following: Tableau, Power Bi, Alteryx, Spotfire, or other BI intelligence tools. Preferred Qualifications While not required, the following qualifications are preferred: Expertise in EMR/Health IT, disease libraries, and insurance claims databases. Proficiency in clinical data standards, clinical 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 with alternative data sources and alternative methods for clinical data collection, particularly those enabled by technology platforms and/or solutions. Experience with trial design, Bayesian modeling, sequential data, computational statistics. Understanding of statistical and machine learning techniques, ability to continue self-learning of technical and non-technical skills. Career Growth Opportunities and Learning Benefits At arenaflex, we are committed to supporting the growth and development of our employees. As a Data Scientist, you will have access to a range of training and development opportunities, including: Professional development workshops and conferences. Mentorship programs with experienced data scientists and industry experts. Opportunities to work on high-impact projects and collaborate with cross-functional teams. Access to cutting-edge tools and technologies, including data analytics software and machine learning platforms. Work Environment and Company Culture arenaflex is a dynamic and innovative organization that values collaboration, creativity, and diversity. Our company culture is built on a foundation of respect, empathy, and open communication, and we are committed to creating a work environment that is inclusive, supportive, and stimulating. As a remote employee, you will be part of a virtual team that is connected through regular video meetings, instant messaging, and collaborative project management tools. Compensation, Perks, and Benefits arenaflex offers a competitive compensation package, including a hourly rate of $27/hour, as well as a range of perks and benefits, including: Flexible working hours and remote work arrangements. Comprehensive health insurance and retirement savings plans. Generous paid time off and holiday policies. Access to employee assistance programs and mental health resources. Opportunities for professional development and career advancement. Conclusion If you are a motivated and talented data scientist looking for a challenging and rewarding role in the healthcare industry, we encourage you to apply for this part-time remote opportunity at arenaflex. With a strong foundation in data analysis and a passion for using data to drive meaningful change, you will be an integral part of our team and contribute to the development of innovative solutions that improve patient outcomes and advance medical research. Apply now to join our team and take the first step towards a rewarding and challenging career in data science. Apply for this job