About careerzynith – Pioneering Health Innovation from Anywhere
careerzynith is a global leader in health‑focused retail and digital services, delivering pharmacy, wellness, and technology solutions to millions of customers each day. Founded over a century ago, careerzynith has evolved from a traditional pharmacy chain into a data‑driven health ecosystem that leverages real‑world evidence (RWE) to shape the future of patient care, drug development, and health economics. Our mission is to empower individuals to lead healthier lives while providing partners in the pharmaceutical and biotech industries with actionable insights that accelerate innovation.
As a remote‑first organization, careerzynith embraces flexible work arrangements, cutting‑edge collaboration tools, and a culture that celebrates curiosity, integrity, and impact. Whether you are joining from Orlando, a coastal city, or a rural town, you will be part of a diverse, inclusive community that values your expertise and encourages continuous learning.
Role Overview – Information Researcher (Real‑World Evidence)
careerzynith is seeking a highly motivated Information Researcher – Real‑World Evidence (RWE) to join our Clinical Data Science team. In this role, you will design, execute, and interpret rigorous data analyses that transform raw health data into certifiable evidence supporting clinical research, health‑technology assessments, and strategic decision‑making for pharmaceutical partners. You will work remotely, collaborating closely with clinical scientists, epidemiologists, and data engineers to deliver insights that drive better health outcomes.
This position reports directly to the Chief, Clinical Data Science and is a critical component of the broader Clinical Research Operations group. You will be expected to apply advanced analytical methods, maintain data integrity, and communicate findings to both technical and non‑technical audiences.
Key Responsibilities
- Data Extraction & Normalization: Mine raw data sets from internal careerzynith repositories and external licensed platforms, transform them into analysis‑ready patient cohorts, and ensure consistent data definitions across projects.
- Collaborative Insight Generation: Partner with clinical researchers, epidemiologists, and external biotech sponsors to translate real‑world observations into actionable evidence for drug efficacy, safety, and health‑economic evaluations.
- Data Lake Management: Clean, curate, and store structured and unstructured data in a centralized data lake, enabling downstream analytics and cross‑functional reuse.
- Statistical & Machine Learning Analyses: Conduct descriptive, predictive, and causal analyses using techniques such as regression modeling, propensity score matching, survival analysis, time‑series forecasting, and unsupervised learning.
- Methodology Development: Design robust, reproducible analytical pipelines that meet regulatory standards for real‑world evidence generation (e.g., FDA, EMA, ISO).
- Quality Assurance: Uphold the highest standards of data quality, documentation, and auditability, ensuring that all deliverables are traceable and reproducible.
- Reporting & Visualization: Build interactive dashboards, detailed reports, and presentation decks for internal stakeholders and external partners, using tools such as Power BI, Tableau, or Spotfire.
- Vendor & Data Source Evaluation: Assess new real‑world data vendors, conduct data quality assessments, and recommend strategic data acquisition decisions.
- Regulatory & Compliance Support: Align analytical work with Good Clinical Practice (GCP), data privacy regulations (HIPAA, GDPR), and industry standards for evidence generation.
- Continuous Learning: Stay abreast of emerging methodologies in epidemiology, health economics, and AI‑driven analytics, and share knowledge across the team.
Essential Qualifications
- Bachelor’s degree in a quantitative discipline (e.g., Statistics, Biostatistics, Computer Science, Mathematics, Epidemiology, or related field).
- Minimum 2‑3 years of experience designing and executing robust statistical analyses for health‑related data, preferably in an RWE or observational research setting.
- Proficiency with statistical software (R, SAS, Stata, or Python) and experience applying advanced methods such as mixed‑effects models, survival analysis, and propensity scoring.
- Hands‑on experience handling large, multi‑source data sets (claims, EMR, registries, or device data) and ensuring data privacy and security.
- Strong knowledge of data visualization and business intelligence tools (Power BI, Tableau, Spotfire, or similar).
- Excellent written and verbal communication skills, with the ability to translate complex analytical results into clear, actionable insights for diverse audiences.
- Demonstrated ability to work independently in a remote environment while maintaining strong collaboration with cross‑functional teams.
Preferred Qualifications & Additional Skills
- Advanced degree (PhD, MSc) in Biostatistics, Epidemiology, Health Economics, Computer Science, or a related discipline.
- Experience with electronic medical record (EMR) systems, health‑insurance claims data, and clinical data standards (ICD‑9/10, SNOMED CT, Read Codes).
- Familiarity with regulatory guidelines for real‑world evidence (e.g., FDA’s RWE framework, EMA guidelines, ISO 14155).
- Exposure to cloud‑based data platforms (AWS, Azure, GCP) and data engineering concepts such as ETL pipelines and data lake architecture.
- Knowledge of machine learning libraries (scikit‑learn, TensorFlow, PyTorch) and their application to health data.
- Experience with Bayesian modeling, hierarchical modeling, or advanced causal inference techniques.
- Ability to develop and maintain reproducible research workflows using version control (Git) and containerization (Docker).
- Strong project management skills, including the ability to prioritize multiple projects, meet deadlines, and communicate progress to stakeholders.
Core Skills & Competencies for Success
- Analytical Rigor: A meticulous approach to data cleaning, validation, and statistical testing.
- Problem‑Solving Mindset: Ability to identify knowledge gaps, formulate research questions, and design appropriate analytical strategies.
- Collaboration & Influence: Skilled at building relationships with clinicians, data engineers, and external partners to drive consensus on study design and interpretation.
- Communication Excellence: Proficiency in crafting clear, concise reports and delivering compelling presentations to both scientific and business audiences.
- Adaptability: Comfort with evolving data sources, emerging analytical tools, and shifting regulatory landscapes.
- Ethical Stewardship: Commitment to patient privacy, data security, and ethical use of health information.
Career Growth & Learning Opportunities
careerzynith invests heavily in the professional development of its employees. As an Information Researcher, you will have access to:
- Mentorship from senior data scientists and clinical research leaders.
- Sponsored certifications (e.g., Certified Clinical Data Scientist, SAS Advanced Programming, AWS Certified Data Analytics).
- Internal learning portals offering courses on advanced epidemiology, health economics, AI in healthcare, and regulatory science.
- Opportunities to present findings at industry conferences, publish in peer‑reviewed journals, and contribute to white papers.
- Clear career pathways toward senior data scientist, lead epidemiologist, or analytics manager roles within careerzynith’s global research organization.
Work Environment & Culture at careerzynith
careerzynith fosters a culture that blends scientific rigor with a supportive, inclusive atmosphere. Our remote workforce enjoys:
- Flexible scheduling that respects work‑life balance, with core collaboration hours to accommodate global teams.
- A virtual community of practice where employees share best practices, celebrate successes, and mentor one another.
- Regular virtual town halls, wellness challenges, and social events that keep remote employees connected.
- Commitment to diversity, equity, and inclusion—ensuring every voice is heard and valued.
- State‑of‑the‑art collaboration tools (Microsoft Teams, Slack, Confluence) that enable seamless communication across time zones.
Compensation, Perks & Benefits
careerzynith offers a competitive hourly rate of $26 per hour, reflecting the expertise required for this role. In addition to base compensation, you will receive a comprehensive benefits package that includes:
- Medical, dental, and vision coverage with flexible spending accounts.
- Prescription drug discounts at careerzynith pharmacies.
- Generous paid time off (vacation, sick leave, and holidays) and a flexible remote‑work stipend.
- Retirement savings options (401(k) with employer match).
- Employee assistance program (EAP) providing confidential counseling and support services.
- Professional development budget for conferences, certifications, and continuing education.
- Wellness initiatives such as virtual fitness classes, health screenings, and mental‑health resources.
- Employee discounts on careerzynith products and services.
How to Apply – Join careerzynith’s RWE Team Today
If you are passionate about turning real‑world health data into evidence that shapes the future of medicine, we want to hear from you. Bring your analytical expertise, collaborative spirit, and curiosity to careerzynith, and help us drive meaningful impact for patients worldwide.
To submit your application, click the link below and follow the simple steps to upload your resume, cover letter, and any relevant work samples. We review applications on a rolling basis and will contact qualified candidates for an initial virtual interview.
Apply Now – Become a Part of careerzynith’s Innovative RWE Team!