About careerzynith
careerzynith stands at the forefront of healthcare innovation, where data meets clinical discovery to transform patient outcomes. As a leading player in the pharmaceutical and healthcare analytics landscape, careerzynith is committed to advancing medical research through the power of real-world evidence (RWE) and cutting-edge data science. Our mission is to bridge the gap between clinical trials and real-world healthcare data, enabling biopharmaceutical companies, healthcare providers, and research institutions to make informed decisions that improve patient care.
With a strong foundation in healthcare analytics, careerzynith has established itself as a trusted partner in the clinical research ecosystem. Our team of data scientists, clinical researchers, and healthcare professionals work collaboratively to unlock insights from complex healthcare data, driving innovation in treatment patterns, patient outcomes, and healthcare economic modeling.
When you join careerzynith, you become part of a dynamic organization that values intellectual curiosity, technical excellence, and a passion for improving healthcare outcomes. We foster a culture of continuous learning, innovation, and collaboration, where your contributions directly impact the future of healthcare analytics and clinical research.
The Role: Real-World Evidence Data Scientist
careerzynith is seeking an experienced Real-World Evidence Data Scientist to join our Scientific Affairs team. In this pivotal role, you will be responsible for generating Real-World Evidence (RWE) through advanced analysis and innovative methodologies in the clinical trials space. As a key member of our Scientific Affairs group, you will influence internal and external decision-making through the application of innovative data science and technology.
This position offers a unique opportunity to work at the intersection of healthcare, data science, and clinical research, contributing to meaningful advancements in medical treatments and patient care. Your work will directly impact how biopharmaceutical companies understand treatment effectiveness, patient populations, and healthcare economic burdens.
Key Responsibilities
- Data Mining and Analysis: Mine raw data sets to deliver standardized, analysis-ready patient cohorts from in-house data resources or licensed platforms, analyze and interpret results, and assist in shaping analysis strategy.
- Cross-Functional Collaboration: Partner with members of the careerzynith Clinical Trial teams to deliver meaningful insights from real-world, clinical, and other data sources to support biopharmaceutical RWE and clinical trial requests. Potential initiatives include analysis of unmet needs, safe and effective treatment in specific disease states, treatment patterns and healthcare economic burden, and cost-effectiveness modeling.
- Data Management: Clean, transform, and store data into an integrated data lake for future analysis and broader team utilization.
- Statistical Analysis: Perform data mining and statistical analysis to analyze RWE/RWD to discover new insights regarding patient populations and treatment outcomes.
- Platform Development: Support the development of real-world data, analytics, and platform capabilities, applying advanced analytics and tools to address scientific questions from biopharmaceutical companies.
- Research Study Design: Collaborate on the design and execution of outcomes research studies.
- Quality Assurance: Ensure high quality, comprehensive, and readily interpretable results from RWE studies and analyses.
- Visualization and Reporting: Build dashboards, analytics, and reports for internal and external use.
- Data Vendor Management: Conduct due diligence on new real-world data provider vendors and drive RWD quality evaluations to inform project decisions.
Essential Qualifications
- Experience: Demonstrated experience in designing and executing robust and reproducible statistical analyses in the context of epidemiology and observational research with healthcare data.
- Statistical Knowledge: Strong knowledge of common statistical testing methods including generalized linear models, clustering and discrimination, decision trees, unsupervised learning, time series analysis, and survival analysis.
- Data Handling: Experience handling large data from diverse data sources.
- Data Privacy: Experience handling protected health information (PHI) with strict adherence to privacy regulations.
- Technical Skills: Proficiency in at least one of the following: Tableau, Power BI, Alteryx, Spotfire, or other business intelligence tools.
Preferred Qualifications
- Education: PhD or Master's degree in statistics, biostatistics, computer science, mathematics, systems engineering, biomedical engineering, or related field.
- Healthcare IT Expertise: Expertise in EMR/Health IT, disease registries, and insurance claims databases.
- Clinical Terminology: Proficiency in clinical data standards, clinical terminologies, and controlled vocabularies used in healthcare data and ontologies (ICD9/10/ReadCode).
- Regulatory Knowledge: Experience in Good Clinical Practice (GCP) as well as regulatory compliance requirements for real-world evidence studies or clinical trials (e.g., ISO, MDD/MDR, CFR).
- Alternative Data Sources: Experience working with alternative data sources and alternative methods for clinical data collection, particularly those enabled by technology platforms and/or solutions.
- Advanced Analytical Methods: Experience with experimental design, Bayesian modeling, sequential data, computational statistics.
- Continuous Learning: Understanding of statistics and machine learning methods, ability to continue self-learning of technical and non-technical skills.
Skills and Competencies for Success
Successful candidates for this position will demonstrate a unique blend of technical expertise, healthcare knowledge, and analytical thinking. Key competencies include:
- Technical Proficiency: Strong programming skills (Python, R, or similar) for data manipulation, analysis, and visualization.
- Healthcare Acumen: Deep understanding of healthcare systems, clinical research processes, and medical terminology.
- Problem-Solving: Ability to translate complex healthcare questions into analytical approaches and deliver actionable insights.
- Communication: Excellent written and verbal communication skills to present complex data findings to both technical and non-technical stakeholders.
- Attention to Detail: Meticulous approach to data quality, analysis, and reporting.
- Collaboration: Ability to work effectively in cross-functional teams and build strong working relationships.
Career Growth Opportunities
At careerzynith, we are committed to the professional development of our team members. As a Real-World Evidence Data Scientist, you will have numerous opportunities for growth and advancement:
- Technical Advancement: Access to cutting-edge data science tools, technologies, and methodologies in the healthcare space.
- Industry Leadership: Opportunity to present research at conferences and contribute to industry publications.
- Career Progression: Clear pathways to senior and leadership positions within the data science and scientific affairs teams.
- Specialization: Opportunities to develop expertise in specialized areas such as specific therapeutic areas, advanced statistical methods, or healthcare economic modeling.
- Mentorship: Access to senior data scientists and industry experts who can provide guidance and career advice.
Work Environment and Company Culture
careerzynith prides itself on fostering a collaborative, innovative, and inclusive work environment. Our culture is built on the following principles:
- Innovation: We encourage creative thinking and continuous improvement in everything we do.
- Collaboration: Cross-functional teamwork is at the heart of our approach to solving complex healthcare challenges.
- Impact: We measure success by the impact we have on healthcare outcomes and patient care.
- Integrity: We maintain the highest ethical standards in all our data handling and research practices.
- Diversity: We value diverse perspectives and backgrounds, recognizing that they enrich our solutions and approaches.
Compensation, Perks, and Benefits
careerzynith offers a comprehensive compensation package designed to attract and retain top talent in the healthcare analytics field:
- Competitive Salary: $26 per hour with opportunities for performance-based increases.
- Health Benefits: Comprehensive medical, dental, and vision insurance for you and your family.
- Flexible Work Arrangements: Remote work options to support work-life balance.
- Professional Development: Generous budget for continuing education, conferences, and certifications.
- Retirement Planning: 401(k) plan with employer matching to help you secure your financial future.
- Wellness Programs: Access to wellness resources, fitness stipends, and mental health support.
- Generous Paid Time Off: Competitive vacation, sick leave, and paid holidays.
- Employee Assistance Program: Confidential counseling and support services for you and your family.
Why Join careerzynith?
When you join careerzynith as a Real-World Evidence Data Scientist, you're not just taking a job – you're embarking on a career that makes a tangible difference in healthcare. You'll work with data that impacts real patients, contributes to medical advancements, and shapes the future of healthcare delivery.
Our commitment to innovation, professional growth, and meaningful work makes careerzynith an ideal place for data scientists who want to apply their skills to healthcare challenges. Whether you're early in your career or an experienced professional, you'll find opportunities to learn, grow, and make an impact.
Apply Today
If you're passionate about using data science to advance healthcare and meet the qualifications outlined above, we encourage you to apply for the Real-World Evidence Data Scientist position at careerzynith. Join us in our mission to transform healthcare through the power of data and analytics.
Your expertise in healthcare data analysis, statistical methodologies, and clinical research will be instrumental in driving our work forward. We look forward to reviewing your application and learning more about how you can contribute to careerzynith's mission of improving patient outcomes through data-driven insights.