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Clinical Data Analyst Bootcamp

Ready to Take Your Career to the Next Level? Become a Statistical Programmer Analyst!

In A Nutshell

The clinical research industry is growing at an exponential rate. It pairs data science and biostatistics to introduce new pharmaceutical products to the market and save people’s lives. If you’re a working professional who would like to transition into a meaningful career, our Statistical Programmer Analyst Training program is worth considering.

Through our in-house, hybrid-style training program, you can receive the specialized knowledge and skills you need to become a successful data science professional in the life science industry.

As you complete this 4-month bootcamp, you’ll be transitioned to the real clinical research projects working with leading life science companies worldwide. Upon completion of the program, you’ll be able to:

  • Build clinical datasets from the clinical database.
  • Communicate with an internal team to create deliverables for pharmaceutical and biotechnology clients.
  • Implement analyses specified in the protocol or the Statistical Analysis Plan (SAP) while working with the project statistician.
  • Write programs to generate tables, listings, and figures and analysis datasets.
  • Validate the programmed analysis datasets, tables, listing and figures.
  • Prepare clinical and statistical summary reports.
  • Utilize programming skills within the protocol team and perform all programming required for clinical trial analysis and reporting.
  • Perform quality control on final reports.

Comprehensive, Full-Time Training Program

4-months training, including hands-on project work

Variety of Cutting-Edge Statistical Software

SAS®, R, SQL, and other modern tools

Work on Top-Priority Clinical Studies

Help save lives and make a positive difference

Full-time Employment at Intego Clinical

Use your math skills for top-priority clinical studies

How To Apply

Join a global biometrics CRO company focused on the future of statistical analysis of clinical trials

Ideal candidates for this program are financial analysts with banking or financial industry experience who would like to apply their knowledge of data analysis to clinical research. Other qualified candidates include graduates from various IT programs with knowledge of SQL and programming languages who wish to enhance their careers.

We also welcome SAS® or R programmers with no previous experience in clinical research and life science. In addition, all candidates must have at least an intermediate level of English and demonstrate clear written and verbal communication with peers, customers, and management.

Apply online. (All applications are free of charge.)
Undergo a face-to-face technical interview with a representative from Intego Clinical.

Once you've been accepted, you’ll officially be on your way to a lucrative career in data science!

Career Opportunities

Statistical Programmer Analysts are professionals who apply mathematical skills and statistical software to comprehensive data analysis in medicine, biology, life sciences and many other related fields.

Clinical Research Organizations

Including Intego Clinical

Pharmaceutical Companies


SAS® Analytics Opportunities

In banking, finance, retail, etc.

Statistical Programmer Analyst Training Program

You’ll be paired with Senior Professionals, Subject Matter Experts and Industry Leaders from Intego Clinical.

This robust training program is delivered to small groups of 3 to 6 trainees through a combination of in-person classes, online sessions, self-study, and project work. Upon completion, successful graduates will gain further, meaningful employment within the company.

Training Program Curriculum


This course is designed to teach students how to execute SAS® programs in a Microsoft Windows environment. It provides an overview of the SAS® system under Microsoft Windows and a fundamental grounding in the following: SAS® DATA step, basic data manipulation including reading raw data into SAS®, using formats and informants, functions, conditional processing, subsetting and joining data sets. The course is also designed to cover the basic reporting procedures, including PROC Print, PROC Freq, PROC Means, PROC Tabulate and PROC Report, as well as the output delivery system (ODS), SQL, SAS®/GRAPH, macros, arrays and other Base SAS® procedures. This course provides a solid grounding in the more advanced features of SAS®.


This course acts as an introduction to the fundamental concepts and approaches that govern the design, analysis and interpretation of clinical research studies. It provides a basic overview of the clinical research industry and new drug development. Students will be introduced to the language that is typically associated with clinical research and the pharmaceutical industry. They will have an opportunity to learn, understand and apply this terminology in the context of clinical research. This course also covers an overview of the process of new drug development from discovery through regulatory to approval and introduction to the market. It’s designed to provide students with the background needed to pursue a number of additional courses in the areas of biostatistics, clinical data analysis and biostatistical programming.


This course provides foundations of database systems, focusing on basics such as relational algebra and data modeling, schema normalization, query optimization and transactions. It teaches the algebraic query language that forms the formal foundations of SQL as well as SQL advanced features.


This course is designed to prepare students to communicate effectively in English within the pharmaceutical industry. This course will equip learners with the linguistic skills and special vocabulary required to understand daily situations in a work environment. A variety of engaging topics and motivating role-plays, as well as an extensive number of practical exercises, will provide students with an understanding of how to communicate effectively in the different areas of the pharmaceutical industry.


This course is highly relevant for modeling and data analysis in many areas, including medicine, actuarial science, economics and other social sciences. Statistics II covers classic repeated measures models, random effect models, generalized estimating equations (GEEs), hierarchical models and transitional models for binary data, marginal vs. mixed effects models, model fitting, model checking, clustering and implications for study design. The module also includes discussion of missing data techniques, Bayesian and likelihood methods for GLMs and various fitting algorithms such as maximum likelihood and generalized least squares. This course also provides an introduction to methods for time-to-event data with censoring mechanisms. Topics include life tables, nonparametric approaches (e.g., Kaplan-Meir, log-rank), semi-parametric approaches (e.g., Cox model), competing risks (introduction to Poisson regression as connection to the Cox model) and time-dependent covariates. Additionally, the methodology and rationale for Bayesian methods and their applications will be briefly discussed.


This course is designed to be very hands-on and focused on the practical aspects of performing clinical trial analyses in the pharmaceutical industry. Skills will include creating datasets, tables and listings, preparing graphics, and performing commonly used statistical analysis. Important topics such as CDISC, MedDRA, WHODrug and SOPs, and other industry regulations and standards, will also be presented to the students during the course. During the workshops, students will import and export raw data files, manipulate and transform data, combine SAS® data sets, perform analysis, create basic detail and summary reports using SAS® procedures, identify and correct data, syntax and programming logic errors and use output delivery systems. Health-related data sets will be provided for students to use.


The data interpretation module is designed to help students who have no background in life sciences prepare for data interpretation assessments in clinical practice. It explores a number of key topics in medicine. Each topic is set around an image or investigation, such as vital signs, an X-ray, CT scan or blood film, that is used to test identification and interpretation of the data provided. Through explanation of the correct and incorrect answers, students can learn from their mistakes in a safe setting. This course aims to teach students how to interpret clinical data and the outputs generated during the Clinical SAS® Programming module.

Frequently Asked Questions

General Questions
Application Process
Further Employment

General Questions

How many positions are available?

Currently, there are up to six trainee positions available.

How long does this training program last?

This is a four month program taught in a hybrid-style format, with online training and in-person training at our offices in Kyiv and Kharkiv. It’s a full-time commitment with an expected workload of 40 hours per week.

Will I get paid for participating in this program?

Yes, you will be a full-time employee who will get paid during training.

What if I decide I no longer want to pursue a career in the pharmaceutical and life science field after this program?

No problem! You will still find the program beneficial as it will increase your knowledge of SAS® and statistical analysis, making you qualified for a successful career in other industries, such as finance and banking, retail and logistics, and many others.

Why SAS®?

SAS® is internationally regarded and sets the industry standard in clinical trial analysis. It is also the only product that has been officially approved by the FDA as a format for clinical data. You can find more information about the applications for SAS® in life science and other industries by clicking here.

Apply Now for The Clinical Data Analyst Bootcamp

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