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About The Company
Pearson is a global leader in education, technology, and data-driven solutions dedicated to transforming learning and assessment. With a rich history of innovation, Pearson leverages cutting-edge data analytics and research to enhance educational outcomes and support the healthcare industry through advanced clinical data solutions. Committed to fostering a diverse and inclusive environment, Pearson strives to empower its employees and partners to make a meaningful impact across various sectors worldwide.
About The Role
We are seeking a highly skilled Data Scientist specializing in Data and Analytics to join our dynamic team. In this role, you will be instrumental in executing exploratory and confirmatory analyses on clinical trial and real-world datasets. Your insights will directly influence clinical strategies and trial designs, ensuring that our solutions meet the highest standards of accuracy and relevance. You will design and implement complex data analysis plans, translating your findings into clear, actionable recommendations for clinical and product stakeholders. The position requires a proactive individual capable of rapidly prototyping analytical workflows using agile practices and DevOps principles, facilitating iterative development and continuous improvement. Additionally, you will define cohorts, design subpopulation analyses, and perform quality assurance to ensure the integrity and robustness of outcomes and datasets. Your expertise will also contribute to harmonizing clinical concepts across various data models such as CDISC SDTM/ADaM, OMOP, and HL7, supporting the mapping and transformation of data for seamless integration and analysis. Collaboration with engineering teams to operationalize analyses on platforms like Databricks is essential, alongside producing reproducible, well-documented code in Python, R, and SQL. Your ability to present complex findings in a clear, tailored manner to stakeholders with varying levels of data literacy will be vital in driving informed decision-making and strategic planning.
Qualifications
The ideal candidate will possess over five years of relevant experience in data analysis within clinical or real-world data environments. Specifically, you should have 3–5 years of hands-on experience working with clinical trial datasets, electronic health records (EHRs), registries, or claims data. Proficiency in Python, R, and SQL for data analysis, reporting, and creating production-ready, reproducible, and well-documented code is essential. A strong background in statistical modeling, machine learning, and deep learning techniques is required, along with familiarity with clinical data standards such as CDISC (SDTM, ADaM), OMOP, and HL7. Experience in data standards mapping, clinical trial design, and operations will be highly valued. Knowledge of enterprise data platforms like GitHub and Databricks for scalable analytics and collaboration is also necessary. The candidate should demonstrate expertise in defining cohorts, conducting subpopulation and stratified analyses, and establishing quality assurance checks for analytical outputs. Comfort working with heterogeneous, imperfect clinical data and delivering timely, high-quality insights despite data challenges is crucial.
Responsibilities
- Execute exploratory and confirmatory analyses on clinical trial and real-world datasets to inform clinical strategy and trial design.
- Design and implement complex data analysis plans, translating findings into actionable insights for clinical and product teams.
- Rapidly prototype MVPs and analytical workflows using agile methodologies and DevOps practices, fostering iterative development with stakeholders.
- Define patient cohorts, design subpopulation analyses, and perform quality assurance to ensure data accuracy and reliability.
- Ensure clinical concepts are accurately represented and harmonized across data models such as CDISC SDTM/ADaM, OMOP, and HL7, contributing to mapping and transformation logic.
- Produce reproducible, well-documented code in Python, R, and SQL, collaborating with engineering teams to operationalize analyses on platforms like Databricks or similar.
- Present findings and recommendations clearly to stakeholders, tailoring communication to varying levels of data literacy and ensuring strategic alignment.
Benefits
At Pearson, we believe in supporting our employees' growth and well-being. We offer competitive compensation packages, comprehensive health benefits, and opportunities for professional development. Our flexible work environment encourages work-life balance, with options for remote work and flexible hours. Employees gain access to ongoing training programs, mentorship opportunities, and participation in innovative projects that make a real impact in healthcare and education sectors. We foster a collaborative and inclusive culture that values diversity, creativity, and continuous learning, ensuring our team remains motivated and engaged in delivering excellence.
Equal Opportunity
Pearson is an equal opportunity employer. We are committed to creating a diverse environment and are proud to be an inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We believe that diverse perspectives and experiences foster innovation and drive success, and we welcome applicants from all backgrounds to join our team.
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