Over 90% of clinical trials fail. The antidote? There is none, but an early detection can prevent cost overruns of millions of dollars. And that's where I come in.I am a young bioinformatician with internships in the pharmaceutical industry, where I have gained familiarity with CDISC standards, clinical trial designs and Agile software developing frameworks. After +3 years of international experience collaborating in diverse data science teams across disease research, drug discovery and early drug development, these are the big industry challenges that have captured my interest:►𝐒𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐢𝐳𝐢𝐧𝐠 𝐝𝐚𝐭𝐚. Alongside my experience involves working with SDTM, ADAM and genetic cohorts; conducting QC tests, implementing imputation strategies for missing data, and digitization of Real World Data (RWD).►𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐧𝐠 𝐚𝐧𝐚𝐥𝐲𝐬𝐞𝐬. I enjoy programming in R, Python and SAS. And I count with experience in Linux, shell scripting and High Performance Computing (HPC). But beyond programming, I recognize the significance of possessing robust statistical foundations, having completed over 20 courses in areas such as causal inference, Bayesian statistics and epidemiology. ►𝐒𝐡𝐚𝐫𝐢𝐧𝐠 𝐤𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞. My interest for science communication involves written (@P-Hackers) and audiovisual (@Bio_100) content. My biochemical bachelor's, leads me to delve into topics such as immunology, omics or pharmacometrics (PKPD). Additionally, I count with experience as teacher assistant in courses of programming languages such as R or Python.In essence, I am excited in all the opportunities that involve innovation in pharma. Feel free to visit my GitHub below and check my coding projects, R packages or Streamlit / R Shiny applications. Don't hesitate to reach out if you have a project that could benefit from an extra hand. I'm all ears!