Remote Real‑World Evidence Data Scientist – Advanced Analytics for Clinical Trials – $26‑35/hr – careerzynith

About careerzynith

careerzynith is a leading global health‑care and retail pharmacy organization with a heritage of more than 170 years serving communities across the United States, Puerto Rico, and the U.S. Virgin Islands. With nearly 9,000 retail locations and a robust omnichannel presence, careerzynith delivers an integrated blend of in‑store and digital experiences, leveraging cutting‑edge technology to bring high‑quality pharmacy and health services to millions of customers every day. Our mission is simple yet powerful: to improve lives by helping people be healthier. As part of our commitment to innovation, careerzynith invests heavily in real‑world evidence (RWE) research, partnering with biopharma companies, academic institutions, and health‑system stakeholders to generate actionable insights that shape the future of medicine.

Why This Role Matters

In the rapidly evolving landscape of clinical research, real‑world data (RWD) has become a cornerstone for understanding treatment effectiveness, safety, and value in everyday practice. As a Remote Real‑World Evidence Data Scientist at careerzynith, you will be at the heart of this transformation. Your analytical expertise will drive evidence‑generation initiatives that inform regulatory decisions, support health‑economic models, and ultimately accelerate the delivery of innovative therapies to patients who need them most.

Key Responsibilities

• Data Acquisition & Integration: Extract, clean, transform, and load diverse data sources—including electronic medical records (EMR), claims databases, disease registries, and proprietary careerzynith data lakes—into a unified analytics environment.
• Analytical Design & Execution: Design robust, reproducible statistical analyses for observational studies, epidemiologic investigations, and health‑economic evaluations using R, Python, or SQL.
• Insight Generation: Conduct advanced data mining, machine‑learning, and statistical modeling to uncover patterns related to patient cohorts, treatment outcomes, safety signals, and cost‑effectiveness.
• Collaboration & Stakeholder Engagement: Partner with clinical trial teams, biopharma sponsors, epidemiologists, and health‑policy experts to translate raw data into actionable insights that address unmet medical needs.
• Dashboard & Reporting Development: Build interactive visualizations and executive‑level dashboards (Tableau, Power BI, Spotfire, or Alteryx) that communicate findings clearly to both technical and non‑technical audiences.
• Quality Assurance & Compliance: Ensure all deliverables meet the highest standards of scientific rigor, data integrity, and regulatory compliance (GCP, ISO, CFR, MDD/MDR).
• Methodology Innovation: Evaluate emerging RWD sources and analytical techniques, recommending enhancements to careerzynith’s data science platform and analytical toolbox.
• Mentorship & Knowledge Sharing: Guide junior analysts, share best practices, and contribute to internal training programs that elevate the overall analytical capability of the Clinical Data Science group.

Essential Qualifications

• Bachelor’s or Master’s degree in a quantitative discipline (e.g., Statistics, Biostatistics, Computer Science, Mathematics, Engineering, Biomedical Engineering).
• Minimum of four years of professional experience in a quantitative or computational role, with a proven track record of delivering high‑impact analytics in health‑care or related fields.
• Proficiency in at least two of the following programming languages: R, Python, SQL.
• Demonstrated experience designing and executing reproducible statistical analyses for epidemiologic or observational studies, including familiarity with generalized linear models, classification & discrimination techniques, decision trees, unsupervised learning, time‑series analysis, and survival analysis.
• Hands‑on experience processing large‑scale data sets from multiple sources, ensuring data quality, consistency, and privacy compliance.
• Solid understanding of health‑care data standards and vocabularies (e.g., ICD‑9/10, SNOMED CT, Read Codes) and experience working with protected health information (PHI) in a secure environment.
• Experience with business intelligence tools such as Tableau, Power BI, Alteryx, Spotfire or comparable platforms for building dashboards and visual analytics.

Preferred Qualifications

• Ph.D. or advanced degree in Biostatistics, Epidemiology, Computer Science, Biomedical Engineering, or a closely related field.
• Deep expertise in EMR/Health‑IT systems, disease registries, and claims databases.
• Knowledge of clinical data standards (e.g., HL7, FHIR) and experience mapping data to standardized ontologies.
• Familiarity with Good Clinical Practice (GCP) and regulatory frameworks governing real‑world evidence generation (e.g., FDA RWE guidance, EMA guidelines).
• Experience designing and analyzing Bayesian models, sequential trials, or adaptive experimental designs.
• Proven ability to work with cloud‑based data platforms (AWS, Azure, GCP) and big‑data processing frameworks (Spark, Hadoop).
• Strong communication skills, with the ability to convey complex analytical concepts to both scientific and business audiences.

Core Skills & Competencies

• Analytical Rigor: Ability to think critically, formulate hypotheses, and apply appropriate statistical methods to derive reliable conclusions.
• Technical Agility: Comfortable navigating multiple programming languages, data‑engineering pipelines, and visualization tools.
• Collaboration: Proven track record of working cross‑functionally with clinicians, data engineers, product managers, and external partners.
• Problem‑Solving: Proactive in identifying data gaps, proposing innovative solutions, and iterating on analytical approaches.
• Ethical Stewardship: Commitment to data privacy, security, and ethical use of patient information.
• Continuous Learning: Enthusiasm for staying current with emerging methodologies in machine learning, causal inference, and health‑economics.

Career Growth & Learning Opportunities

careerzynith invests heavily in the professional development of its employees. As a Remote Real‑World Evidence Data Scientist, you will have access to:

• Mentorship from senior data scientists and industry thought leaders.
• Sponsored certifications (e.g., Certified Health Data Analyst, AWS Certified Data Analytics).
• Opportunities to present research at national conferences and publish in peer‑reviewed journals.
• Cross‑functional project rotations that broaden exposure to regulatory affairs, product development, and health‑policy analysis.
• Leadership pathways that can lead to senior scientific roles, analytics management, or strategic advisory positions within careerzynith’s global research network.

Work Environment & Culture at careerzynith

Our culture is built on collaboration, curiosity, and a shared purpose to improve health outcomes. Whether you are working from a home office or a local coworking hub, you will be part of a diverse, inclusive community that values:

• Flexibility: Fully remote work arrangements with flexible hours to support work‑life balance.
• Innovation: An environment that encourages experimentation, rapid prototyping, and data‑driven decision making.
• Impact: Direct contribution to projects that influence drug development, payer decisions, and patient care pathways.
• Diversity & Inclusion: Programs and employee resource groups that celebrate varied perspectives and foster belonging.
• Well‑Being: Access to mental‑health resources, wellness challenges, and a supportive leadership team.

Compensation, Perks & Benefits

careerzynith offers a competitive hourly rate ranging from $26 to $35 per hour**, depending on experience and qualifications. In addition to base compensation, you will receive a comprehensive benefits package that includes: