Data Manager II - R Programming (Scientific/Clinical Data)

Simulations Plus stands as a premier provider in the biopharma sector, offering advanced software and consulting services that enhance drug discovery, development, research, clinical trial operations, regulatory submissions, and commercialization. Our comprehensive biosimulation solutions integrate artificial intelligence/machine learning, physiologically based pharmacokinetics, physiologically based biopharmaceutics, quantitative systems pharmacology/toxicology, and population PK/PD modeling approaches. We also deliver simulation-enabled performance and intelligence solutions alongside medical communications support for clinical and commercial drug development. Our cutting-edge technology is licensed and utilized by leading pharmaceutical, biotechnology, and regulatory agencies worldwide.Leadership truly cares about maintaining a positive culture and employee well-being. We offer fully remote work, flexible schedules, and generous vacation policy along with affordable health coverage, stock options, annual bonus, and more! Check out how much our employees love working here: https://www.comparably.com/companies/simulations-plus.The Data Manager II will provide efficient and effective programming solutions while receiving high-level direction to perform a wide range of data management activities. The role is expected to independently execute assigned tasks, manage data complexity, and deliver high-quality outputs in support of scientific and project objectives.Department: OperationsInternal Grade: 9Direct Reports: NoStatus: ExemptLocation: Remote in PolandThis position is based in Poland and supports global project teams. While the long‑term objective of this role is to contribute to expanded global‑clock coverage, the individual will be expected to work a second‑shift schedule for an initial period (anticipated up to one year) to provide overlap with USA based teams and ensure continuity of project delivery.Job Responsibilities: Comprehend major components of study protocols to understand study designs and execution as they pertain to data management activitiesInterpret case report forms and match them against datasets to identify problems and questionsIdentify missing information based upon understanding of client’s study protocols and data collectedBegin to identify and understand original data without client-provided data documentationBegin to identify derived variables by examining data and verify or confirm variablesMay create drafts of basic requirement documentsCreate datasets based upon study protocols, data analysis plans and requirements with guidance from more senior data managersCreate simple datasets (for example, Phase I, single studies using nominal times)Create pharmacokinetic and pharmacodynamic datasets to be used in different analysis solutions, including NONMEM, WinNonlin, and MonolixCreate complex datasets that include studies with complex designs and complicated data relationships, under supervision of more senior data managersCreate dummy datasets based upon provided requirementsCreate simulation datasets based upon guidance from more senior data managersUnderstand and apply rules provided for data file creation for different modeling solutionsUnderstand and apply concept of data dispositionReconcile records from original to analysis datasetCreate data deletion datasets to track deleted records based upon identified edit rulesReview data disposition section of final technical reportProvide programming support to meet project objectivesWrite efficient code to meet project needs and seek guidance from more senior data managers on when to use advanced codingRead in raw data files and SAS datasetsCreates listing, summary, HTML, and graph output and consult with more senior data managers to utilize advance featuresInvestigate and summarize data by generating frequency tables and descriptive statisticsCreate variables and reassign data values, subsets data, and combines multiple filesDevelop and use standardized programs to facilitate the automation of routine programming tasksDesign, write, and debug macro routines and understand how programs with and without macro code are processedBegin to understand the sources of universal macro code data input (for example, SAS datasets, NONMEM table files)Begin to understand how to analyze and troubleshoot data sources; reviews data to provide input on data analysis plan directionPerform exploratory data analyses using requirements provided by scientists or specified in data analysis plans and summarize findings with guidance from more senior data managers.While working under general supervision, understand and apply more advanced statistical tests including parametric and non-parametric inferential statistical testing methods, measures of correlation/association, probability distributions, hypothesis testing, analysis of variance, and linear regressionDemonstrated foundational proficiency in the use of AI assisted tools to support data analysis, programming, and quality review activities. This includes the ability to:Use AI tools to accelerate exploratory data analysis, code development, and problem solvingCritically evaluate and validate AI generated outputsApply sound judgment to ensure accuracy, reproducibility, and compliance with established data management and quality standardsCreate and maintain project documentation in accordance with all standard operating proceduresTest all output to ensure it meets needs of project teams, based upon provided requirements and changes to requirementsPerform additional testing of dataset creation, based upon knowledge of dataset content and stratification criteriaDocument pertinent programs written as part of an external projectFollow Quality Management System procedures for file storage and naming conventionsFollow standards for variable name and value assignment as defined by senior data managers and documented standardsAssist in testing and documentation of new and revised software applicationsParticipate in project teams while following direction from the Data Management lead and/or project leaderEnsure an appropriate level of communication with internal team membersUnderstand changes in project direction, whether communicated verbally, electronically, or in writingCommunicate information to senior data managers and work with more senior data managers when there are questions or problems with dataProvide advice and make recommendations about data to scientists Perform project management activities for assigned taskIdentify changes to timelines to determine impact upon assignments and meet the new deadlinesChange direction of programming activities to accommodate project changes to ensure minimal interruptionUnderstand study characteristics: for example, long-term objectives, data, and specific information, such as what population is being usedMay act as data management lead on a project for which there are several data managers, under supervision from more senior data managersIdentify and explore opportunities for professional development and trainingAttend internal and external training opportunitiesRemain current with technical readingReview material in industry-related publications regarding new methodologies and best practices performed by other companies, as identified by more senior data managersContribute to departmental roundtableProvide internal training and make internal presentationsAssist in developing presentations for external conferences and meetingsIdentify complex problems and provide recommendations based upon analysis of the situation for assigned projectsMake decisions that impact tasks of an assigned projectTrack time through project management systemOrganize tasks and utilizes in-house management tools to ensure most efficient use of timeComply with all policies and standard operating procedures as specified in the Quality Management SystemOther duties as assigned Qualifications: 2+ years of experience using R for data manipulation, analysis, and reporting in a scientific or analytical environmentFoundational familiarity with AI-assisted analytical or coding tools, with the ability to apply them thoughtfully and validate results in regulated or scientific contextsRead and interpret manuals and technical documents and to communicate this interpretation effectivelyAble to work with base R, tidyverse, or data.table, ggplot2Extremely detail-orientedHighly self-motivated and willing to take on challengesAble to handle multiple tasks simultaneouslyAble to work within tight deadlinesPossess effective critical-thinking, problem-solving, and organizational skillsEffective verbal and written communication skillsEffective presentation skillsPossess effective relationship-building skills with the ability to work closely with project leaders and team membersWork well independently with the demonstrated ability to work as a member of a teamOccasional travel for meetings and trainings Education: Bachelor’s degree in statistics, math, or related fieldMasters or PhD in statistics, math, or related field a plusFind out more about how amazing it is to work at Simulations Plus by visiting www.simulations-plus.com/career-center and apply today!

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