About the Role
careerzynith is partnering with a forward-thinking healthcare organization to hire a talented Remote Data Scientist – Real-World Evidence & Clinical Analytics who is passionate about transforming raw medical and clinical data into meaningful, life-changing insights. This is not a traditional data entry or administrative position — it is a high-impact opportunity for a quantitative professional to apply cutting-edge data science techniques within the rapidly evolving clinical trials and real-world evidence (RWE) space.
As a member of the Scientific Affairs team, you will play a central role in supporting biopharmaceutical partners, internal stakeholders, and external collaborators by uncovering trends, patterns, and outcomes hidden deep within large, complex healthcare datasets. Your work will directly influence strategic decision-making, shape patient treatment paradigms, and contribute to the development of safer, more effective therapies for diverse patient populations.
If you thrive in a remote-first environment, love solving puzzles buried in massive data lakes, and want your technical skills to translate into real-world clinical impact, this role at careerzynith is built for you.
Key Responsibilities
As a Remote Data Scientist focused on Real-World Evidence at careerzynith, your day-to-day work will blend advanced analytics, statistical modeling, and cross-functional collaboration. Your core responsibilities will include:
- Data Curation & Cohort Development: Transform raw, heterogeneous data sets into standardized, analysis-ready patient cohorts sourced from in-house data assets or qualified external systems. Interpret results carefully and help shape the broader analytics strategy for the team.
- Cross-Functional Partnership: Work closely with members of the Clinical Trial and Scientific Affairs teams to deliver actionable insights drawn from real-world, clinical, and adjacent data sources. These insights will support biopharmaceutical RWE initiatives and clinical trial requests, including analyses of unmet medical needs, treatment patterns, healthcare economic burden, cost-effectiveness modeling, and safe use of therapies in specific disease states.
- Data Engineering & Integration: Clean, transform, and load data into an integrated data lake architecture to support future analyses and broader organizational consumption. Ensure data integrity, consistency, and accessibility for downstream users.
- Statistical & Predictive Analytics: Perform data mining, exploratory analysis, and rigorous statistical modeling on RWE and real-world data (RWD) to surface new insights about patient populations, treatment outcomes, and disease progression.
- Platform & Capability Development: Support the evolution of real-world data, analytics, and platform capabilities by applying advanced analytical methods and modern tools to address complex clinical questions raised by biopharmaceutical collaborators.
- Outcomes Research Collaboration: Collaborate on the design and execution of outcomes research studies, contributing methodological rigor and analytical depth to research protocols and publications.
- Quality & Interpretability: Ensure all RWE deliverables meet the highest standards of scientific rigor, reproducibility, and interpretability — producing outputs that are defensible, clear, and useful for both technical and non-technical audiences.
- Dashboarding & Reporting: Build intuitive dashboards, analytics, and reports for both internal stakeholders and external partners, ensuring insights are accessible and actionable.
- Data Diligence & RWD Quality Assessment: Conduct due diligence on prospective real-world data vendors and lead RWD quality assessments to inform strategic sourcing and investment decisions.
Basic Qualifications
To succeed in this role, candidates should bring a strong quantitative foundation and demonstrated hands-on experience with modern data science tools:
- Education: Bachelor’s or graduate degree in a quantitative, computational, or related discipline, plus a minimum of four (4) years of experience in a quantitative, analytical, or computational role.
- Programming Proficiency: At least four (4) years of hands-on experience using R, Python, or SQL for data analysis and modeling.
- Statistical Analysis Experience: Demonstrated ability to design and execute robust, reproducible statistical analyses within the context of epidemiology, observational research, or healthcare data studies.
- Statistical Knowledge: Working knowledge of common statistical testing methods, including generalized linear models, classification and discrimination techniques, decision trees, unsupervised learning, time series analysis, and survival analysis.
- Big Data Processing: Experience processing large, complex datasets drawn from diverse data sources.
- Healthcare Data Familiarity: Experience handling protected patient health information (PHI) in compliance with applicable privacy and security standards.
- BI & Visualization Tools: Working knowledge of at least one business intelligence platform such as Tableau, Power BI, Alteryx, Spotfire, or comparable tools.
Preferred Qualifications
Candidates who stand out will likely bring advanced credentials and specialized experience in healthcare and clinical research analytics:
- Advanced Degree: Ph.D. or Master’s degree in biostatistics, statistics, computer science, mathematics, systems engineering, biomedical engineering, or a closely related field.
- EMR & Health IT Expertise: Hands-on experience with electronic medical records (EMR), health information technology systems, disease registries, and insurance claims databases.
- Healthcare Data Standards: Deep familiarity with clinical data standards, medical terminologies, and controlled vocabularies commonly used in healthcare datasets and ontologies (e.g., ICD-9, ICD-10, ReadCode).
- Regulatory & Compliance Knowledge: Experience with Good Clinical Practice (GCP) and/or regulatory compliance guidelines for real-world evidence studies or clinical trials, including standards such as ISO, MDD/MDR, and CFR.
- Alternative Data Sources: Experience working with novel or alternative data sources and modern methods of clinical data collection, particularly those enabled by digital health technologies and connected platforms.
- Advanced Modeling: Practical experience with experimental design, Bayesian modeling, sequential data analysis, and computational statistics.
- Continuous Learner: Strong understanding of statistical and machine learning methodologies, with a demonstrated ability to continuously self-educate on both technical and non-technical topics.
Skills & Competencies for Success
Beyond technical qualifications, the ideal candidate will bring a balanced mix of analytical, communication, and collaboration skills:
- Strong problem-solving mindset with the ability to approach ambiguous, complex questions with structured thinking.
- Excellent written and verbal communication skills — capable of translating technical findings into clear, compelling narratives for non-technical stakeholders.
- Detail-oriented approach with a passion for producing high-quality, reproducible work.
- Self-motivated and comfortable thriving in a fully remote work environment.
- Collaborative team player who enjoys partnering across scientific, clinical, and business functions.
- Curiosity-driven attitude with a commitment to continuous learning in a fast-moving field.
Career Growth & Learning Opportunities
At careerzynith, we believe the best work happens when talented professionals are given the space, resources, and mentorship to grow. As a Data Scientist on this team, you will have the opportunity to:
- Work on challenging, high-visibility projects that directly impact patient outcomes and biopharmaceutical strategy.
- Build deep expertise in real-world evidence, clinical analytics, and healthcare data science — one of the fastest-growing areas in data-driven medicine.
- Collaborate with seasoned scientific, clinical, and technical leaders who are invested in your professional development.
- Access ongoing training, conferences, and certification opportunities to expand your technical and domain knowledge.
- Progress into senior individual contributor or leadership roles as our analytics organization continues to scale.
Work Environment & Company Culture at careerzynith
careerzynith is committed to fostering an inclusive, innovative, and human-centered workplace — even in a fully remote setting. Our culture is built on collaboration, curiosity, accountability, and a shared mission to improve health outcomes through better data. We celebrate diverse perspectives, encourage open dialogue, and believe that great ideas can come from anywhere. When you join careerzynith, you join a team that values your voice, respects your time, and trusts you to do your best work from wherever you are.
Compensation, Perks & Benefits
This role offers a competitive hourly rate of $26–$35/hour, commensurate with experience and qualifications. In addition, careerzynith-supported positions typically include a comprehensive benefits package that may feature:
- Company-paid life insurance
- Medical, prescription drug, dental, and vision coverage
- Retirement savings plan (401(k))
- Employee stock purchase plan
- Generous paid time off (PTO) and holiday schedule
- Paid parental leave (PPL)
- Transportation benefit plan
- Employee store discount
- Voluntary life and personal accident insurance
(Specific benefits may vary depending on the partnering organization, but careerzynith works closely with employers to ensure comprehensive support for every team member.)
How to Apply
If you are a quantitative professional with a passion for healthcare, data science, and real-world evidence — and you are excited by the opportunity to do meaningful, remote-first work — we want to hear from you. Bring your curiosity, your technical skill, and your drive to make a measurable impact, and join careerzynith as we help shape the future of evidence-based medicine.
Apply today and start your next chapter with careerzynith.
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