Robert Rachford’s Post

🍂 Autumn’s here, and just like the leaves, the projects in pharma and life sciences are piling up fast! 🍁 Biostatisticians, Data Managers, and Statistical Programmers are in high demand as teams work hard to bring critical insights to life. Who else is “fall-ing” for those Q4 deadlines? 🙋♂️ If you're ready to embrace the season of crunch time and want to jump into an impactful role (or know someone who does), let’s connect! #Recruitment #LifeSciences #Biostatistics #StatisticalProgramming #Autumn

Good opportunity

Becoming a Sr. Reviewer is a BIG jump in the career journey of a biostatistician. Here are some key things I think about anytime I am conducting a Sr. Review of TLF Shells: In the career journey of a biostatistician, a major milestone is hit when you get your first Sr. Reviewer Assignment. You are not the lead statistician on the project, instead you are the Sr. Reviewer and are responsible for ensuring everything put forward by the lead statistician is accurate and makes good statistical sense for the project. One of the major items you will review as the Sr. Reviewer will be the TLF Shells. The TLF shells are the document that will highlight for the study team what the outputs will look like once all the data is collected and all the analyses are run. (The word "shell" is very appropriate here - the shell is the structure or casing that all the results (analyzed data) will fill at the end of the study). During the Sr. Review of TLF Shells, I HIGHLY recommend you keep the following items in mind: 1️⃣ Are all analyses called for in the SAP included in the shells? Have the SAP open and go through each shell and ensure there is a place in the SAP where that specific analysis is described. This is for all Shells. If it's a table, listing, or figure, there should be some mention in the SAP for that analysis. 2️⃣ Does each individual shell convey a clear and understandable story? The question to ask yourself here is "Would someone who is unfamiliar with this study or this data be able to walk up to this output and understand the story it is trying to tell? 3️⃣ Do all tables working in concert tell a clear, understandable and complete story? This one is a little more difficult to review at the shell stage as there is no data yet but the main thesis here is to think about what information is contained within one shell and which other shells would contain similar data and how easy would it be for someone to evaluate that data across those outputs. 4️⃣ Are there any analyses missing that you would expect to see? Similarly, can any of the proposed tables be updated to be figures? These two are often overlooked by Sr. Reviewers who are just looking at the shells presented to them and not thinking about the bigger picture or the end goal (ensuring the study is setup to achieve it's primary and secondary objectives if the IP works). 5️⃣ What statistical assumptions are going to be made to run these analyses and does it make sense to present any of the measures (degrees of freedom for example) within the shells? The Sr. Reviewer is a critical role in the process flow for creating good and usable shells. Please feel free to reach out with any questions you have about these best practices and please feel free to share your own best practices - this community is always looking to lean! Happy Saturday

Should companies take steps to train their statisticians / data scientists/ biostatisticians on their products? To my surprise a number of managers in industry see these experts generically: they have the skills, ergo, they can analyze any product situation. In my view, such hires are at risk of becoming technicians who need to be closely micromanaged since they don't really understand the commercial context, to formulate good business relevant questions for analysis. Take to the extreme, why not have a biostatistician analyze air traffic control data despite the fact they know nothing about air traffic control. If managers want insight from these hires, they have to invest in ensuring they are trained on the product area in question and deal with analytics problems in the same product area over time.

📌Sharing some of my newly gained experiences from the very beginning 🩺..... . ➡️. .... ... 💻 ⚕️As a #medical professional, I never thought of transition into the #DataAnalyst field. However, I realized that data-driven insights could revolutionize healthcare, and I wanted to be a part of it. I applied my analytical mind and attention to detail, skills I developed in medicine, to data analysis. 🖊️The #transition wasn't easy, but my medical training provided a solid foundation. I adapted my skills to learn new tools, programming languages, and statistical techniques and discovered that working with datasets are somehow similar to treating #patients – diagnosing issues, developing treatment plans, and monitoring progress. 🖊️My #medical experience also helped me understand the human side of data. I consider the stories behind the numbers, just as I did with patients. This unique perspective allows me to bridge gaps between healthcare domain and data domain. 🖊️I've come to realize that my transition wasn't a _departure from medicine_ but an evolution. I'm still driven by the same passion to improve lives, now using data as my primary tool. My medical background brings a distinct viewpoint to #data #analysis, and I've found a new way to make a difference. ↩️Moral of the story➡️ Learning in a continuous process, anywhere from any point, it is standardized. #DataAnalyst #Data #medico #NurseToDataAnalyst #Careertransition

Read my blog on the PHUSE website- The Roles of Statisticians in Data Safety Monitoring Boards (DSMBs) and Interim Analysis Whether you are a fresher or an experienced Statistician, it is always beneficial to revisit the basics and comprehend the diverse role of a biostatistician in a clinical trial. Understanding the roles and responsibilities involved is crucial. Explore more about the roles of statisticians in data safety monitoring boards (DSM Bs) and interim analysis here #PHUSE #PHUSEBLOG #industrytopics #statisticalanalysis #DSMB

FINAL CALL! 📣 This is a last call to find writers for the biostatistics[.]ca platform! What does it entail? 1 - Send me a DM. 2 - You write a single article. No additional commitment for now, although we have plans to eventually hire experts as staff writers. 3 - We post the article to the platform, share it on the biostatistics[.]ca Linkedin page and on my profile. 4 - The post can include a professional picture, a short bio and a link to something biostatistics-related you would like to promote (a blog, a paper, etc.). This is a great way to contribute to the biostatistics community online. We've onboarded a few writers already and we're excited to showcase their articles very soon! The next round will probably be towards the end of 2024. Huge thanks to all of you who support this project :) #biostatistics #statistics #data #science #blog

Clinical SAS - Career Guidance Webinar #ClinicalSAS #ClinicalTrials #PharmaData #Biostatistics #CDISC #SASProgramming #ClinicalDataManagement #StatisticalAnalysis #DrugDevelopment #PharmaceuticalResearch #FDACompliance #ClinicalResearch #SASAnalytics #CRFDesign #SDTM #ADaM #PharmaSAS #DataAnalysis #ProtocolDesign #StatisticalModeling

#hiring *Biostatistician Quality Improvement (Full Time, Day shift)*, Miami, *United States*, fulltime #opentowork #jobs #jobseekers #careers #Miamijobs #Floridajobs #ScienceTechnology *Apply*: https://lnkd.in/gVybuTz5 Description Job Summary Supports clinicians and collaborators by assisting with study design, data analysis, and results interpretation. Manages quality improvement projects and supports interpretation of large data sets. Provides project specific support for statistical analysis and validation. Job Specific Duties Provides data management, statistical analysis, and programming for ongoing and proposed studies including lab, quality improvement research, experimental, and observational studies. Collaborates with study teams and applies statistical, computational, and scientific expertise during the design, implementation, and reporting phases of these studies. Assists with the computation and written description of appropriate sample size, sampling, and randomization procedures. Provides primary statistical programming support to refine and implement planned statistical analyses. Manages analysis of datasets, statistical programs, and associated study documents to facilitate replication of results by colleagues & external reviewers. Participates in studies & assists with interpretation & communication of statistical analyses results, preparation of graphical & textual description results for papers, abstracts, & presentations. Provides educational sessions and training to medical trainees and PIs on basic statistical concepts. Qualifications Minimum Job Requirements Master's Degree in Public Health, Epidemiology or Statistics 1-3 years of experience with SAS base/advanced programming, SPSS, Minitab or similar quality improvement software Knowledge, Skills, and Abilities Biostatistician experience preferred Experience using statistical computer languages such Python or R to manipulate data and draw insights from large data sets Experience with using clinical databases such as KID, Vizient or PHIS preferred Prior experience with REDCap, PowerBI, Hadoop, SQL and SAP Business Objects preferred Knowledge of medical terminology; able to understand clinical data from medical records, such as diagnoses and procedure codes, APR-DRG codes, etc. Ability to assist in developing frameworks and processes to build areas of emphasis around Machine Learning and advanced predictive analytics Ability to assist with the development and implementation of innovative statistical approaches to solve complex analytical requirements Ability to function independently, keep track of multiple projects, work to meet specific deadlines, and document procedures is critical Detail oriented, highly motivated, and committed to achieving excellence in the form of productivity and publications Excellent communication and collaborat

#hiring *Biostatistician Quality Improvement (Full Time, Day shift)*, Miami, *United States*, fulltime #opentowork #jobs #jobseekers #careers #Miamijobs #Floridajobs #ScienceTechnology *Apply*: https://lnkd.in/gVybuTz5 Description Job Summary Supports clinicians and collaborators by assisting with study design, data analysis, and results interpretation. Manages quality improvement projects and supports interpretation of large data sets. Provides project specific support for statistical analysis and validation. Job Specific Duties Provides data management, statistical analysis, and programming for ongoing and proposed studies including lab, quality improvement research, experimental, and observational studies. Collaborates with study teams and applies statistical, computational, and scientific expertise during the design, implementation, and reporting phases of these studies. Assists with the computation and written description of appropriate sample size, sampling, and randomization procedures. Provides primary statistical programming support to refine and implement planned statistical analyses. Manages analysis of datasets, statistical programs, and associated study documents to facilitate replication of results by colleagues & external reviewers. Participates in studies & assists with interpretation & communication of statistical analyses results, preparation of graphical & textual description results for papers, abstracts, & presentations. Provides educational sessions and training to medical trainees and PIs on basic statistical concepts. Qualifications Minimum Job Requirements Master's Degree in Public Health, Epidemiology or Statistics 1-3 years of experience with SAS base/advanced programming, SPSS, Minitab or similar quality improvement software Knowledge, Skills, and Abilities Biostatistician experience preferred Experience using statistical computer languages such Python or R to manipulate data and draw insights from large data sets Experience with using clinical databases such as KID, Vizient or PHIS preferred Prior experience with REDCap, PowerBI, Hadoop, SQL and SAP Business Objects preferred Knowledge of medical terminology; able to understand clinical data from medical records, such as diagnoses and procedure codes, APR-DRG codes, etc. Ability to assist in developing frameworks and processes to build areas of emphasis around Machine Learning and advanced predictive analytics Ability to assist with the development and implementation of innovative statistical approaches to solve complex analytical requirements Ability to function independently, keep track of multiple projects, work to meet specific deadlines, and document procedures is critical Detail oriented, highly motivated, and committed to achieving excellence in the form of productivity and publications Excellent communication and collaborat