About the Role
careerzynith is seeking a talented and dedicated Real World Evidence (RWE) Data Researcher to join our dynamic Clinical Data Science team. This is an exceptional opportunity for a data professional who is passionate about leveraging advanced analytics to transform healthcare outcomes and drive meaningful insights in the pharmaceutical and clinical research space. In this role, you will be at the forefront of generating real-world evidence that directly impacts patient care, Treatment innovation, and healthcare decision-making across the industry.
As an Information Researcher at careerzynith, you will serve as a critical member of our Scientific Solutions group, working collaboratively with cross-functional teams to deliver cutting-edge analytical insights. Your expertise in data science, statistics, and healthcare analytics will help us address complex business questions that shape the future of clinical trials and biopharmaceutical research. This position offers the chance to work with diverse data sources, including electronic medical records, insurance claims, and patient outcomes data, all while contributing to studies that have the potential to improve millions of lives worldwide.
Key Responsibilities
- Data Mining and Preparation: Extract and transform raw datasets from internal data sources and authorized platforms to create standardized, analysis-ready patient cohorts that support advanced research initiatives.
- Statistical Analysis and Interpretation: Conduct sophisticated data analysis to interpret results, identify trends, and help shape overall research strategies that align with business objectives and scientific goals.
- Cross-Functional Collaboration: Partner with various members of the careerzynith Clinical Trials team to deliver meaningful insights from real-world, clinical, and other data sources that support biopharmaceutical RWE and clinical trial requests. This includes analysis of unmet needs, safety and efficacy of treatments in specific disease states, treatment patterns, and healthcare economic burden.
- Cost-Effectiveness Modeling: Participate in cost-effectiveness modeling and health economic assessments to evaluate Treatment Value in various therapeutic areas.
- Data Lake Management: Clean, transform, and store data into a organized data lake infrastructure for future analysis and broader team utilization, ensuring data quality and accessibility.
- Advanced Analytics: Perform data mining and statistical analysis on RWE/Real-World Data (RWD) to discover new insights regarding patient populations and treatment outcomes.
- Capacity Development: Support the development of real-world data, analytics, and platform capabilities by applying advanced analysis tools and methodologies to address scientific inquiries from biopharmaceutical clients.
- Outcomes Research: Collaborate on the design and execution of health outcomes research studies that generate high-quality, reproducible evidence.
- Quality Assurance: Ensure superior-grade, thorough, and readily interpretable outputs from RWE reviews and investigations, maintaining the highest standards of data integrity.
- Reporting and Visualization: Build dashboards, analyses, and comprehensive reports for both internal and external stakeholders to communicate findings effectively.
- Vendor Evaluation: Conduct due diligence on new real-world data suppliers and vendors, driving RWD quality assessments to inform investment decisions and partnership strategies.
Essential Qualifications
Education and Experience
- Bachelor's degree in statistics, biostatistics, mathematics, computer science, or a related quantitative field is required; advanced degrees (Master's or PhD) are strongly preferred.
- Proven experience in designing and executing robust and reproducible statistical studies in the context of epidemiology and observational research with healthcare data.
- Demonstrated experience handling large datasets from multiple data sources including EMR, claims, and registry data.
- Experience working with protected patient health information (PHI) in compliance with HIPAA and other privacy regulations.
Technical Skills
- Proficiency in statistical programming languages such as R, Python, or SAS is required.
- Strong knowledge of statistical testing methods including generalized linear models, classification and regression, decision trees, unsupervised learning, time series analysis, and survival analysis.
- Expertise in at least one of the following business intelligence and visualization tools: Tableau, Power BI, Alteryx, Spotfire, or other BI insight tools.
- Familiarity with database query languages (SQL) and cloud-based data platforms.
- Understanding of clinical data standards, clinical terminologies, and controlled vocabularies used in healthcare data and ontologies (ICD-9/10, ReadCode, SNOMED CT).
Preferred Qualifications
- Advanced degree (Master's or PhD) in statistics/biostatistics, computer science, mathematics, systems engineering, biomedical engineering, or a related quantitative field.
- Proficiency in EMR/Health IT systems, disease registries, and insurance claims datasets with deep understanding of healthcare data architecture.
- Experience in Good Clinical Practice (GCP) as well as regulatory compliance guidelines for real-world evidence studies or clinical trials (e.g., ISO standards, MDD/MDR, CFR Title 21).
- Demonstrated experience working with alternative data sources and alternative methods for clinical data collection, especially those enabled by technology platforms and digital health solutions.
- Background in study design, Bayesian modeling, sequential analysis, and computational statistics.
- Strong understanding of machine learning and AI methodologies, with the capacity to continue self-learning of both technical and non-technical skills.
- Knowledge of pharmaceutical or biotech industry workflows and familiarity with clinical trial design and execution.
Skills and Competencies
- Analytical Thinking: Strong problem-solving skills with the ability to approach complex data challenges methodically and develop innovative solutions.
- Communication Skills: Excellent written and verbal communication skills to effectively present technical findings to both technical and non-technical audiences.
- Collaboration: Strong teamwork and collaboration skills with the ability to work effectively in cross-functional teams.
- Attention to Detail: Meticulous attention to data quality and accuracy with commitment to producing high-quality work.
- Time Management: Ability to manage multiple projects and deadlines simultaneously while maintaining quality standards.
- Adaptability: Quick learner who stays current with emerging technologies, analytical methodologies, and industry trends.
- Initiative: Self-motivated professional who takes ownership of projects and drives them to completion with minimal supervision.
Career Growth and Learning Opportunities
At careerzynith, we believe in investing in our people's professional development and career advancement. As a Real World Evidence Data Researcher, you will have access to comprehensive training programs, mentorship opportunities, and the chance to work on diverse projects that span multiple therapeutic areas and data types. We support continuous learning through internal knowledge-sharing sessions, conference attendance, and advanced certification programs.
Our team structure promotes organic career progression, and top performers have advanced into senior analytical roles, team lead positions, and specialized consulting roles within the organization. You will gain exposure to cutting-edge analytics methodologies, real-world data sources, and pharmaceutical industry best practices that will position you for long-term career success in the growing field of health data science.
Work Environment and Culture
careerzynith boasts a collaborative, inclusive, and innovation-driven work environment where diverse perspectives are valued and celebrated. Our team culture emphasizes scientific rigor, intellectual curiosity, and a commitment to excellence in everything we do. We foster a supportive atmosphere that encourages open communication, creative thinking, and professional growth.
As part of our team, you will enjoy flexible work arrangements, including remote work options that support work-life balance. Our modern office spaces are equipped with state-of-the-art technology and collaborative spaces that facilitate teamwork and innovation. We host regular team-building activities, scientific symposiums, and social events that build strong connections across the organization.
Compensation and Benefits
careerzynith offers a competitive compensation package that reflects the value we place on talent and expertise. The expected salary range for this position is $20-30 per hour, depending on experience, qualifications, and internal equity considerations. We also offer a comprehensive benefits package that includes:
- Health, dental, and vision insurance coverage
- 401(k) retirement plan with company matching contributions
- Paid time off (PTO) and flexible spending accounts
- Professional development funding and tuition reimbursement
- Employee assistance program (EAP) and wellness resources
- Performance-based bonus opportunities
- Stock options or equity participation programs for eligible employees
Why Join careerzynith?
careerzynith is at the forefront of transforming healthcare through data-driven insights. By joining our team, you will contribute to meaningful work that improves patient outcomes, advances medical science, and shapes the future of healthcare. We are committed to creating an environment where talented individuals can thrive, grow, and make a lasting impact.
If you are passionate about leveraging data science to solve complex healthcare challenges and want to be part of a team that values innovation, collaboration, and excellence, we encourage you to apply for this exciting opportunity. Take the next step in your career and join careerzynith where your analytical skills can make a real difference.
How to Apply
Interested candidates who meet the qualifications and are excited about the opportunity to contribute to cutting-edge healthcare analytics are encouraged to apply. Please submit your application through our online portal, including your resume, cover letter, and any relevant portfolio or work samples that demonstrate your analytical capabilities.
careerzynith is an equal opportunity employer dedicated to fostering diversity and inclusion in the workplace. We welcome applicants from all backgrounds and experiences and are committed to providing reasonable accommodations to individuals with disabilities during the application and hiring process.