Offer summary

Qualifications:

Master’s degree in statistics, biostatistics, epidemiology, mathematics, computer science, or other quantitative fields; a doctoral degree is preferred., Minimum 5 years of experience with SAS programming in public health areas such as Epidemiology or Biostatistics., Good knowledge of data science and familiarity with digital technologies like LLM, ML, DL, ANN, NLP., Excellent communication, analytical skills, and ability to work independently or as part of a team..

Key responsabilities:

Lead statistical analysis and programming for epidemiologic projects using SAS, R, SQL, and Python.

Manage databases to ensure timely completion of pharmacoepidemiologic projects and address related issues.

Collaborate with experts to implement new methods and technologies in epidemiology and safety-sciences.

Stay updated on new developments in programming and analytic methods.

Job description

When our values align, there's no limit to what we can achieve.

At Parexel, we all share the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market access, every clinical development solution we provide is underpinned by something special - a deep conviction in what we do.

Each of us, no matter what we do at Parexel, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with empathy and we're committed to making a difference.

Job Summary:
The primary function of an Epidemiology Analyst is to lead the statistical analysis, programming (for example SAS), and database management for epidemiologic projects for any business unit (GenMed, Spec Care, Vaccine). The analysts also lead the implementation of new advanced methods, technology and innovations in epidemiology and safety-sciences to improve health outcomes, focusing on demonstrating the safety of our products. Additionally, analyst also contribute to the execution and implementation of innovative projects using advanced AI technology.

Knowledge/Skills:
• Extensive knowledge in statistical programming (especially using SAS), database management and statistical analysis.
• Good knowledge of data science to work comfortably using latest digital technology (e.g. LLM, ML, DL, ANN, NLP etc)
• Understanding and experience using US-based real-world data (claims as well as medical record databases)
• Excellent communication and analytical skills as well as a high level of self-motivation, initiative and attention to detail are required.
• Ability to work independently and as a team player, and to work on multiple projects under pressure and with tight timelines.
• Fluent in English.

Education/Experience
• Master’s degree in statistics, biostatistics, epidemiology, mathematics, computer science, or other quantitative fields. A doctoral degree is preferred.
• Extensive experience (minimum 5 years) with SAS programming in public health related areas (e.g., Epidemiology, Biostatistics, or Outcome Research). Experience with other programming languages e.g. python, SQL, R is desirable.
• Experience with various operating systems, including UNIX and Windows operating systems, and structured programming principles and documentation procedures.

Principal Duties/Responsibilities
Lead statistical analysis and programming:
o Lead statistical analysis and programming (for example using SAS, R, SQL, python etc), database management and statistical analysis for epidemiologic projects supporting specific business unit (GenMed, Vaccine, Spec Care).
o Provide documentation of the programs, databases, and systems.

Lead database evaluation and management, and collaborate with the RWD and Information System staff:
o Address database issues related to the data storage, management and analysis.
o Provide support in the evaluation, acquisition, storage and management of databases.
o Manage databases to ensure timely completion of pharmacoepidemiologic projects.

In collaboration with Pharmacoepidemiology and Benefit-Risk experts, lead the implementation of new advanced methods, technology and innovations in epidemiology, benefit-risk and safety-sciences to improve health outcomes.

Keep abreast of new developments in programming and analytic methods and tool