01Overview
About careerzynith Transforming Health & Wellness Through Innovationcareerzynith is a leading, technologydriven health services organization dedicated to delivering personalized, affordable, and highquality care to millions of people across the United States. With a heritage rooted in community pharmacy, retail health, and integrated healthplan management, careerzynith has evolved into a comprehensive health ecosystem that includes retail locations, specialty pharmacy, telehealth, and a robust dataanalytics platform. Our missionCarry our heart to every moment of your healthguides every decision, from the way we design digital solutions to the way we empower our employees to make a meaningful impact.
As a remotefirst employer, careerzynith embraces flexibility, diversity, and continuous learning. We believe that a thriving workforce fuels innovative solutions, and we invest heavily in the professional growth, wellbeing, and inclusion of every team member.
Position Overviewcareerzynith is seeking a detailoriented
Data Entry Analyst Healthcare Data Solutionsto join our Research & Development (R&D) and Analytics team. In this role, you will design, build, and maintain data pipelines, analytical models, and reporting tools that enable the organization to improve operational efficiency, enhance member experiences, and drive strategic decisionmaking across our healthcare portfolio.
This is a fully remote, online position offering a competitive hourly rate of $26, with the flexibility to work from anywhere in the United States.
Key Responsibilities
Data Pipeline Development:Design, implement, and optimize automated data extraction, transformation, and loading (ETL) processes that ingest large volumes of structured and unstructured healthcare data from multiple sources.
Analytical Modeling:Build predictive and prescriptive models using statistical techniques and machine learning algorithms to identify trends, forecast outcomes, and recommend actionable solutions.
Process Improvement:Identify opportunities to streamline claims processing, payment reconciliation, and member enrollment workflows, delivering measurable gains in speed and accuracy.
Data Quality Assurance:Conduct rigorous data validation, cleansing, and integrity checks to ensure the reliability of analytics and reporting outputs.
Visualization & Reporting:Create intuitive dashboards and visualizations using tools such as Tableau, Power BI, or Looker to communicate insights to crossfunctional stakeholders.
Collaboration:Partner with product managers, engineers, clinicians, and business analysts to translate complex business problems into datadriven solutions.
Documentation:Maintain comprehensive documentation of data schemas, pipeline architectures, and analytical methodologies for knowledge sharing and regulatory compliance.
Continuous Learning:Stay current with emerging datascience techniques, healthcare regulations, and industry best practices to continuously enhance the analytical capabilities of the team.
Essential Qualifications
Minimum2 years of professional experiencein data analysis, data engineering, or a related quantitative field.
Proficiency in programming languages such asPython or Rfor data manipulation, statistical analysis, and model development.
Strong command ofSQLfor querying relational databases and optimizing complex queries.
Demonstrated experience working with large healthcare datasets, including claims, pharmacy, or member enrollment data.Ability to interpret and translate business requirements into technical specifications and analytical deliverables.Excellent written and verbal communication skills, with the ability to present technical concepts to nontechnical audiences.Selfstarter mindset with strong organizational skills and the ability to manage multiple priorities in a remote environment.Preferred Qualifications
Advanced degree (M.S. or Ph.D.) in Data Science, Statistics, Computer Science, Health Informatics, or a related discipline.Experience with cloud platforms (AWS, Azure, or Google Cloud) and modern dataengineering tools such as Apache Spark, Airflow, or dbt.Familiarity with healthcare industry regulations (HIPAA, HITECH) and dataprivacy best practices.Knowledge of machinelearning frameworks (scikitlearn, TensorFlow, PyTorch) and experience deploying models into production.Prior exposure to telehealth, specialty pharmacy, or healthplan operations.Core .
