How to Be Postdoctoral Fellow/Biostatistician - Job Description, Skills, and Interview Questions

Oct 5, 2021 / 5 Minutes Read / By Albert

How to Become

Professional Organizations

FAQ

Links

Exposure to career opportunities in biostatistics has been a key factor in driving a steady rise in the number of postdoctoral fellows pursuing this field. As a result, universities and research institutions have seen an increase in the number of highly trained biostatisticians available for hire. This is beneficial for employers, who can capitalize on the expertise of postdoctoral biostatisticians to help advance their research objectives. Furthermore, the increased presence of postdoctoral biostatisticians in the workforce has helped to raise the profile of the field, leading to greater recognition and increased funding for biostatistics-related initiatives.

Steps How to Become

Obtain a Bachelor's Degree. To become a biostatistician, you must first earn an undergraduate degree in statistics, mathematics, or a related field.
Earn an Advanced Degree. To become a postdoctoral fellow or a biostatistician, you must have at least a Master's degree in biostatistics, statistics, or a related field.
Take the Exam. To become a postdoctoral fellow or a biostatistician, you must pass the Certified Biostatistician Exam (CBE). The CBE is offered by the American Statistical Association.
Build Your Professional Network. It is important to build relationships with other biostatisticians, postdoctoral fellows, and researchers in the field. This will help you stay informed about current trends and opportunities and also help you find jobs.
Get Experience. As a postdoctoral fellow or biostatistician, experience is key. You should seek out internships and research opportunities to gain hands-on experience in the field. You can also take courses or workshops to further your knowledge and skills.
Apply for Positions. Once you have the necessary qualifications and experience, you can begin applying for positions as a postdoctoral fellow or biostatistician. Employers usually prefer applicants who have previous experience working in the field.

The quality of a Postdoctoral Fellow/Biostatistician is directly correlated with the reliability and qualifications of the individual. Without the proper qualifications, a Postdoctoral Fellow/Biostatistician will not be able to provide accurate and reliable analysis of data. The most qualified individuals possess a doctoral degree in biostatistics or a related field, as well as expertise in statistical analysis and programming.

Furthermore, they must be able to effectively communicate their findings to other professionals, both verbally and in writing. Without these qualifications, it is impossible to trust the data analysis of a Postdoctoral Fellow/Biostatistician, leading to unreliable research results and conclusions.

You may want to check Senior Biostatistician, Biostatistics Research Scientist, and Biostatistics Consultant for alternative.

Job Description

Develop and implement statistical models to analyze and interpret scientific data
Design and conduct studies to evaluate the effectiveness of medical treatments
Develop and validate statistical methods to support the analysis of health outcomes
Utilize data management systems to store, analyze and present data
Collaborate with other scientists and research teams to identify and assess study objectives
Prepare and interpret reports, tables, graphs and other materials
Manage databases, software programs and statistical packages
Design and implement survey instruments and protocols
Develop and maintain statistical software applications
Participate in grant writing activities

Skills and Competencies to Have

Advanced knowledge of biostatistical modeling and statistical analysis techniques.
Strong knowledge of SAS, R, and/or other statistical software.
Ability to design and conduct clinical trials, observational studies, and epidemiological studies.
Experience with health care databases, such as Medicare/Medicaid, ICD-9/ICD-10 coding, etc.
Knowledge of data visualization techniques and software.
Ability to interpret and present results in a clear and concise way.
Knowledge of ethical and legal issues related to research design and data privacy.
Excellent written and verbal communication skills.
Ability to work independently and collaboratively in a team environment.
Ability to manage multiple projects under tight deadlines.

The ability to apply advanced statistical methods to analyze and interpret data is an essential skill for a Postdoctoral Fellow/Biostatistician. Without a deep understanding of statistics, it is impossible to accurately analyze data and understand the implications of any changes or trends. Having a strong knowledge of statistical theories and methods, such as linear regression, logistic regression, and Bayesian analysis, is key to being able to accurately interpret data and make sound conclusions.

Furthermore, being able to effectively communicate the results of data analysis is also essential. A Postdoctoral Fellow/Biostatistician must be able to clearly explain the findings to other scientists in order to inform further research. Finally, it's important for a Postdoctoral Fellow/Biostatistician to stay up-to-date with the latest advancements in the field in order to provide the most accurate and helpful analysis.

Epidemiologist/Biostatistician, Biostatistics Data Scientist, and Research Biostatistician are related jobs you may like.

Frequent Interview Questions

What motivated you to pursue a Postdoctoral Fellow/Biostatistician position?
What experience do you have working with large datasets?
Describe your experience with data analysis techniques and software programs.
How do you ensure the accuracy of your data analysis results?
Are you familiar with the statistical packages used in biostatistics?
What methods do you use to communicate complex data analysis results to non-technical audiences?
What do you consider to be the most challenging aspect of data analysis?
What challenges have you faced in your previous positions related to data analysis?
How do you approach problem-solving and finding solutions for complex data analysis problems?
Describe a project you are proud of that involved data analysis.

Common Tools in Industry

R programming language. A powerful open-source language for statistical computing and graphics. (e. g. creating statistical models and data visualizations)
SAS. A software suite for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics. (e. g. analyzing large data sets and creating reports)
SPSS. A software package used for statistical analysis, data mining, and text mining. (e. g. creating graphs and charts to visualize data)
Mplus. A statistical software package used for structural equation modeling, latent class analysis, and multilevel modeling. (e. g. creating linear models to analyze complex data sets)
STATA. An integrated statistical software package used for data management, data analysis, and graphics. (e. g. creating regression models to analyze relationships between variables)
Python. A general-purpose programming language used for data science, machine learning, and web development. (e. g. creating machine learning algorithms to analyze complex data sets)

Professional Organizations to Know

American Statistical Association
International Biometric Society
International Statistical Institute
Royal Statistical Society
The Biometric Society
International Society for Bayesian Analysis
International Society for Clinical Biostatistics
American Public Health Association
International Epidemiological Association
Society for Clinical Trials

We also have Biostatistics Data Manager, Clinical Biostatistician, and Health Data Analyst/Biostatistician jobs reports.

Common Important Terms

Statistical Inference. The process of using data to draw conclusions or make predictions about a population.
Descriptive Statistics. The collection and summarization of data to describe the characteristics of the population.
Predictive Analytics. The use of statistical techniques to make predictions about future outcomes based on patterns in existing data.
Machine Learning. The use of algorithms and techniques to automatically learn from data and improve predictions and decisions.
Data Mining. The process of analyzing large datasets to discover patterns and relationships in the data that can be used to make decisions.
Statistical Modeling. The use of mathematical and statistical techniques to develop models that can be used to explain, predict, or control a system.
Experimental Design. The process of planning experiments with control groups and variables in order to test hypotheses and draw conclusions.
Data Visualization. The use of charts, graphs, and other visuals to present data in an easy-to-understand format.

Frequently Asked Questions

Q1: What qualifications are required for a Postdoctoral Fellow/Biostatistician? A1: Applicants for a Postdoctoral Fellow/Biostatistician position typically require a doctoral degree in biostatistics, statistics, epidemiology, or a related field. Knowledge of data analysis software such as SAS, R, and STATA is also necessary. Q2: What type of responsibilities will a Postdoctoral Fellow/Biostatistician have? A2: A Postdoctoral Fellow/Biostatistician is typically responsible for designing and conducting statistical analysis and research projects, developing methods for data collection and analysis, providing statistical guidance for investigators, and providing statistical consultation services to other researchers. Q3: How much does a Postdoctoral Fellow/Biostatistician typically earn? A3: According to the Bureau of Labor Statistics, the median annual wage for biostatisticians in the United States is $88,190. Q4: What type of environment will a Postdoctoral Fellow/Biostatistician work in? A4: Postdoctoral Fellows/Biostatisticians typically work in laboratories or research centers, usually in colleges or universities. Q5: What type of skills are necessary for a successful Postdoctoral Fellow/Biostatistician? A5: Successful Postdoctoral Fellows/Biostatisticians require strong analytical skills, problem-solving skills, communication skills, attention to detail, and the ability to work independently.

Web Resources

Postdoctoral Fellow in Biostatistics | Population Health Sciences phs.weill.cornell.edu
Postdoctoral Fellows | Johns Hopkins | Bloomberg School of publichealth.jhu.edu
Postdoc Fellow - Biostatistics/Bioinformatics/Statistical Genetics ... case.edu