High School

A good foundation for future clinical data management work includes classes in mathematics, science, statistics, history, social studies, and philosophy, which help develop critical-thinking and analytical skills. Take all computer science classes that are offered in your school, especially database management, data analytics, programming, and artificial intelligence. English classes are also essential for honing your communication skills.

Postsecondary Education

Clinical data managers often have a bachelors degree in information technology, computer science, life sciences, business, statistics, data science/analytics, or related fields. College courses focus on mathematics, statistics, research methods, data management programs, science, ethics, and may also include biology, pharmacology, and anatomy. Some employers may hire clinical data managers who have an associates degree coupled with certification as a clinical data manager and prior work experience.

Certification

Many colleges and universities offer undergraduate and graduate certificates in data science, data analytics, business intelligence, and related fields. For example, Georgetown University awards a certificate in data science to those who have a bachelor’s degree or equivalent, and who have completed specific courses. Cornell, Harvard University, Syracuse University, Indiana University at Bloomington, and other colleges and universities offer similar programs. Contact schools in your area for more information.

Other Education or Training

Professional development opportunities are provided by associations, for-profit and nonprofit schools (such as Global Knowledge Training LLC, Coursera, edX, and Udacity), and information technology companies (such as IBM). For example, the Association for Computing Machinery and the IEEE Computer Society offer online courses on data management, project management, and related topics. Other organizations that offer continuing education courses and training are the International Web Association, the American Mathematical Society, American Statistical Society, INFORMS, and DAMA International. Contact these organizations for more information.

Certification or Licensing

Clinical data managers may receive the designation certified clinical data manager from the Society for Clinical Data Management. Certification shows employers that managers have achieved a standard of knowledge, education, and experience that is recognized in the field. To be eligible for certification, candidates must pass the certification examination and meet one of the following educational/experience qualifications:

• have an associates degree and at least three years of full-time experience
• have a bachelors degree and a minimum of two years of full-time experience
• have no degree, but have four or more years of full-time experience as a clinical data manager
• part-time work experience equal to or surpassing full-time equivalent in the above criteria

Other associations that provide certification for data management professionals include TDWI, the Institute for Certification of Computing Professionals, DAMA International, and INFORMS. Contact these organizations for more information.

Most employers of clinical data managers require they have a bachelors degree and two to three years of full-time experience in the field. Clinical data managers must be knowledgeable about computers and software programs. They spend much of their workday gathering, processing, analyzing, and sharing information on computers. They are skilled in using scientific software, classification software, database reporting and user interface software, and medical software. In addition to analytical and critical-thinking skills, clinical data managers must have strong communication skills to effectively convey information to supervisors, peers, subordinates, and others involved in data management projects. Individuals who do best in this type of work are detail oriented, reliable, honest, good-natured and cooperative, and able to solve problems using logic and deductive reasoning.