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About careerzynith – Pioneering Health Innovation at Scale
careerzynith is a leading, globally‑recognized health‑care and retail pharmacy organization that blends cutting‑edge scientific research with everyday wellness solutions. With a heritage that stretches back over a century, careerzynith has evolved from a single storefront into a dynamic network of pharmacies, digital health platforms, and research hubs that serve millions of customers across the United States and beyond. Our mission is to improve health outcomes by turning real‑world data into actionable insights that guide therapeutic decisions, support pharmaceutical partners, and empower patients.
Why This Role Matters
In today’s data‑driven health ecosystem, real‑world evidence (RWE) is the cornerstone of evidence‑based medicine. As a Part‑Time Real‑World Evidence Data Scientist at careerzynith, you will be at the forefront of transforming raw clinical data into credible, regulatory‑grade evidence that influences drug development, reimbursement strategies, and patient‑care pathways. This is a remote‑first position that offers flexibility, competitive compensation, and the chance to collaborate with world‑class clinicians, epidemiologists, and biopharma partners.
Key Responsibilities
- Data Extraction & Normalization: Mine raw data collections from internal electronic health records (EHR), claims databases, and external registries. Convert heterogeneous sources into a standardized, analysis‑ready patient cohort.
- Analytical Pipeline Development: Design, implement, and document reproducible analytical pipelines using R, Python, and SQL to answer high‑impact business questions.
- Collaborative Insight Generation: Partner with careerzynith Clinical Research teams, external biopharma sponsors, and health‑technology partners to translate RWE findings into strategic recommendations.
- Data Lake Management: Clean, transform, and store data in a secure, governed data lake that supports downstream analytics, machine‑learning models, and cross‑functional reporting.
- Statistical & Econometric Analyses: Conduct advanced statistical testing, survival analysis, propensity‑score matching, and health‑economic modeling to assess treatment effectiveness, safety, and cost‑effectiveness.
- Quality Assurance & Compliance: Ensure all analyses meet Good Clinical Practice (GCP), ISO, and regulatory standards for real‑world evidence generation.
- Visualization & Reporting: Build interactive dashboards (Power BI, Tableau, or Spotfire) and comprehensive reports for internal stakeholders and external clients.
- Methodology Innovation: Evaluate emerging data sources (e.g., wearable devices, patient‑generated health data) and incorporate novel analytical techniques such as Bayesian modeling and machine‑learning‑driven pattern discovery.
- Project Leadership: Contribute to study design, protocol development, and execution of RWE projects, ensuring timelines and deliverables are met.
Essential Qualifications
- Bachelor’s degree in a quantitative discipline (e.g., Statistics, Computer Science, Epidemiology, Bioinformatics, or related field). A master’s or PhD is a plus but not required.
- Minimum 2 years of hands‑on experience with at least one of the following programming languages: R, Python, or SQL.
- Demonstrated ability to design and execute robust, reproducible analyses focused on disease epidemiology, treatment patterns, or health‑economic outcomes.
- Solid understanding of statistical testing methods, including regression modeling, clustering, decision trees, unsupervised learning, time‑series analysis, and survival analysis.
- Experience handling large, multi‑source datasets and ensuring data integrity throughout the analytical lifecycle.
- Familiarity with protected health information (PHI) handling, HIPAA compliance, and data‑privacy best practices.
- Proficiency with at least one business‑intelligence tool (e.g., Power BI, Tableau, Alteryx, Spotfire) for creating clear, actionable visualizations.
Preferred Qualifications & Nice‑to‑Have Skills
- Advanced knowledge of EMR/Health‑IT systems, disease ontologies (ICD‑9/10, SNOMED CT, Read Codes) and claims data structures.
- Experience with Good Clinical Practice (GCP) and regulatory compliance frameworks such as ISO 13485, MDD/MDR, or CFR 21 Part 11.
- Background in clinical trial design, Bayesian modeling, longitudinal data analysis, or health‑technology assessment.
- Exposure to AI/ML pipelines, including model development, validation, and deployment for clinical insight generation.
- Strong communication skills with the ability to translate complex statistical concepts into clear business narratives for both technical and non‑technical audiences.
- Self‑directed learner who stays current with emerging data‑science techniques, health‑economics methodologies, and industry trends.
Core Skills & Competencies
- Analytical Rigor: Ability to think critically, question assumptions, and apply rigorous statistical methodology.
- Technical Proficiency: Mastery of data‑wrangling, scripting, and database querying; comfortable with cloud‑based data platforms (AWS, Azure, GCP).
- Collaboration: Proven track record of working cross‑functionally with clinicians, data engineers, and business leaders.
- Communication: Clear written and verbal articulation of findings, recommendations, and technical documentation.
- Ethical Stewardship: Commitment to patient privacy, data security, and ethical use of health data.
- Project Management: Ability to prioritize tasks, manage timelines, and deliver high‑quality results in a part‑time, remote environment.
Career Growth & Learning Opportunities
careerzynith invests heavily in the professional development of its talent. As a part‑time RWE Data Scientist, you will have access to:
- Mentorship from senior data scientists and clinical research leaders.
- Sponsored certifications (e.g., Certified Health Data Analyst, SAS, or AWS Data Analytics).
- Internal learning portals covering advanced statistical methods, health‑economics, and regulatory science.
- Opportunities to transition into full‑time roles, lead independent research projects, or move into strategic advisory positions within careerzynith’s global research network.
Work Environment & Culture at careerzynith
careerzynith embraces a flexible, inclusive, and innovation‑driven culture. Our remote‑first policy empowers employees to work from anywhere in the United States while staying connected through virtual collaboration tools, regular team huddles, and quarterly in‑person meet‑ups. We celebrate diversity, encourage curiosity, and reward initiative. Whether you are a seasoned data professional or an emerging talent, you will find a supportive environment that values work‑life balance, continuous learning, and meaningful impact on public health.
Compensation, Perks & Benefits (General Overview)
- Competitive Hourly Rate: $27 per hour, paid bi‑weekly.
- Flexible Scheduling: Choose shifts that align with your personal commitments; the role is designed for an 8‑hour workday.
- Health & Wellness: Access to medical, dental, and vision plans; employee assistance program (EAP) for confidential counseling.
- Retirement Savings: 401(k) plan with employer matching contributions.
- Employee Discounts: Savings on careerzynith pharmacy services, health‑and‑wellness products, and partner offerings.
- Professional Development: Tuition reimbursement, internal training workshops, and conference attendance support.
- Paid Time Off: Vacation, sick leave, and holidays in accordance with careerzynith policies.
- Technology Stipend: Home office equipment allowance to ensure a productive remote workspace.
How to Apply
If you are passionate about turning real‑world health data into evidence that drives better patient outcomes, we want to hear from you. Join careerzynith’s dynamic RWE team and make a tangible difference in the future of medicine.
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