About careerzynith
careerzynith is a forward-thinking, innovation-driven organization operating at the intersection of healthcare, data science, and pharmaceutical research. With a mission to transform how real-world evidence (RWE) shapes modern medicine, careerzynith partners with biopharmaceutical companies, research institutions, and clinical operations teams to deliver rigorous, reproducible, and actionable insights from large-scale healthcare data. Our work directly influences treatment decisions, health policy, patient outcomes, and the development of life-changing therapies.
Headquartered with a strong national presence and a thriving remote workforce, careerzynith fosters a culture of curiosity, scientific excellence, and collaboration. We believe that data, when wielded with precision and creativity, has the power to redefine patient care. By joining careerzynith, you become part of a multidisciplinary team of clinicians, statisticians, engineers, and epidemiologists who are passionate about turning complex datasets into clear, life-impacting knowledge.
Position Overview
careerzynith is seeking a highly motivated and analytically sharp Real-World Evidence (RWE) Data Scientist to join our Scientific Projects team. This is a remote, full-time opportunity offering a competitive hourly rate of $26/hour. Working standard 8-hour business hours, the successful candidate will design, execute, and interpret sophisticated analyses of clinical, medical, and real-world datasets that inform strategic decisions across the biopharmaceutical and clinical trial landscape.
This role is ideal for a data professional who thrives at the intersection of biostatistics, epidemiology, and healthcare informatics. You will mine raw datasets, build reproducible analytical pipelines, construct dashboards, and partner with cross-functional stakeholders to deliver insights that matter. If you are driven by intellectual challenge and a desire to make a measurable impact on patient health, careerzynith offers the platform to do exactly that.
This position reports directly to the Director of Clinical Data Science and collaborates closely with the broader Scientific Projects, Clinical Trials, and Biopharmaceutical Partnerships teams.
Key Responsibilities
- Mine, cleanse, transform, and store raw datasets from in-house assets and licensed third-party platforms, producing standardized, analysis-ready patient cohorts for downstream use.
- Conduct sophisticated data analyses to address critical business and scientific questions, interpret results, and help shape overall research and analysis strategy.
- Partner with members of the careerzynith Clinical Trials team to deliver actionable insights from real-world, clinical, and complementary data sources supporting biopharmaceutical RWE and clinical trial requests.
- Perform analyses that may include assessment of unmet medical needs, safe and effective treatment patterns within specific disease states, treatment utilization patterns, healthcare economic burden, and cost-effectiveness modeling.
- Cleanse, transform, and integrate data into a unified data lake architecture to enable future analyses and broader team consumption.
- Apply data mining, statistical analysis, and machine learning techniques to RWE and real-world data (RWD) to uncover new insights regarding patient populations, treatment outcomes, and disease trajectories.
- Support the ongoing development of real-world data assets, analytics methodologies, and platform capabilities—applying advanced analytics and modern tools to solve scientific questions posed by biopharmaceutical partners.
- Collaborate on the design and execution of outcomes research studies, contributing to protocol development, methodology selection, and result interpretation.
- Ensure the highest standards of quality, scientific rigor, and interpretability across all RWE studies, analyses, and reports.
- Build, maintain, and refine dashboards, analytic tools, and reports for both internal stakeholders and external biopharmaceutical clients.
- Conduct due diligence on new real-world data providers and vendors, and lead RWD quality assessments that inform strategic sourcing and partnership decisions.
Essential Qualifications
- Bachelor's degree in statistics, biostatistics, computer science, mathematics, epidemiology, systems engineering, biomedical engineering, or a closely related quantitative discipline.
- Proven experience in designing and executing robust, reproducible statistical analyses within the context of epidemiology and observational research using healthcare data.
- Strong working knowledge of common statistical testing methods, including generalized linear models, classification and clustering techniques, decision trees, unsupervised learning methods, time series analysis, and survival analysis.
- Hands-on experience processing and analyzing large datasets drawn from diverse data sources and formats.
- Demonstrated experience handling protected patient health information (PHI) with a clear understanding of data privacy and security best practices.
- Working knowledge of at least one business intelligence or analytics platform such as Tableau, Power BI, Alteryx, Spotfire, or comparable tools.
Preferred Qualifications
- PhD or Master's degree in statistics, biostatistics, computer science, mathematics, systems engineering, biomedical engineering, or a related field.
- Deep familiarity with electronic medical records (EMR) and health IT systems, disease registries, and insurance claims databases.
- Proficiency in clinical data standards, clinical terminologies, and controlled vocabularies used in healthcare data, including ICD-9, ICD-10, Read Code, and related ontologies.
- Experience working within Good Clinical Practice (GCP) guidelines and regulatory compliance frameworks for real-world evidence research or clinical trials, such as ISO, MDD/MDR, or CFR.
- Experience working with alternative data sources and novel methods of clinical data collection, particularly those enabled by modern technology platforms and digital health solutions.
- Experience with experimental design, Bayesian modeling, sequential data analysis, and computational statistics.
- Solid understanding of statistical inference and machine learning techniques, with a demonstrated commitment to continuous self-directed learning of both technical and non-technical skills.
Core Skills and Competencies
- Strong analytical mindset with the ability to translate ambiguous business questions into structured, testable hypotheses.
- Excellent written and verbal communication skills, with the ability to present complex technical findings to non-technical audiences clearly and persuasively.
- Detail orientation and a commitment to scientific rigor, reproducibility, and data integrity.
- Comfort working in a fast-paced, evolving environment where priorities may shift in response to new scientific or business needs.
- Strong collaboration skills and the ability to work effectively within cross-functional teams spanning science, operations, and client engagement.
- Self-starter mentality with the discipline and accountability required to thrive in a remote work setting.
Career Growth and Learning Opportunities
At careerzynith, your growth is a priority. We invest in our people through structured mentorship, internal knowledge-sharing sessions, conference attendance support, and access to cutting-edge training in advanced analytics, biostatistics, and emerging healthcare data technologies. As the company continues to scale, high-performing team members have clear pathways into senior data science roles, team leadership positions, and strategic scientific advisory functions. Whether you aspire to deepen your technical expertise in causal inference and machine learning, or to evolve into a client-facing scientific lead, careerzynith provides the resources, projects, and mentorship to make that journey achievable.
Work Environment and Company Culture
careerzynith is proud to be a remote-first organization that values outcomes over office hours. Our culture is built on trust, transparency, intellectual humility, and a shared commitment to improving patient lives through better evidence. Team members enjoy the flexibility to work from anywhere in the United States while staying deeply connected through regular virtual team syncs, quarterly in-person meetups, and an active internal community of practice. We celebrate diversity of thought, background, and experience, recognizing that the best insights emerge when different perspectives converge around a shared scientific mission.
Compensation, Perks, and Benefits
- Competitive hourly pay at $26/hour, with regular performance reviews and opportunities for compensation growth.
- Comprehensive health coverage, including medical, dental, and vision insurance plans for eligible employees.
- Paid time off for holidays, vacation, and personal days, with accrual based on tenure and role.
- Retirement savings plan with employer matching contributions to help you build long-term financial security.
- Employee assistance program (EAP) offering confidential counseling, wellness resources, and support for personal and professional challenges.
- Wellness programs designed to support physical and mental health, including fitness challenges, health screenings, and access to digital wellness platforms.
- Professional development support, including training budgets, conference sponsorships, and internal upskilling programs.
- Flexible scheduling within a remote-first framework to help you balance work with the rest of your life.
How to Apply
If you are a curious, rigorous, and impact-driven data scientist ready to apply your analytical talents to one of the most meaningful challenges in healthcare, we encourage you to apply today. careerzynith is looking for individuals who are not only technically capable but also genuinely passionate about using data to improve patient outcomes and advance the science of real-world evidence. Bring your expertise, your ambition, and your perspective—and help us shape the future of evidence-based medicine. Join careerzynith, where your work moves beyond the dashboard and into the lives of patients around the world.