Key Facts

Remote From:

Anywhere

Full time

Mid-level (2-5 years)

English

Hard Skills

Other Skills

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Ability To Meet Deadlines
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Multitasking
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Critical Thinking
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Organizational Skills
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Detail Oriented
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Team Building
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Verbal Communication Skills
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Willingness To Learn
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Self-Motivation
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Problem Solving

Roles & Responsibilities

2+ years of experience using R for data manipulation, analysis, and reporting in a scientific or analytical environment.
Proficiency with base R, tidyverse, data.table, and ggplot2.
Foundational familiarity with AI-assisted analytical or coding tools with the ability to apply them thoughtfully and validate results in regulated or scientific contexts.
Excellent attention to detail, strong problem-solving and organizational skills, and ability to manage multiple tasks and meet tight deadlines.

Requirements:

Interpret study protocols and case report forms to guide data management, identify data issues, and reconcile records between original data and analysis datasets.
Create, manage, and document datasets across simple and complex study designs, including pharmacokinetic/pharmacodynamic datasets for analysis tools (NONMEM, WinNonlin, Monolix).
Develop and maintain automated programming solutions, read raw data, generate listings and outputs, write macros, and apply AI-assisted tools for data analysis while ensuring accuracy and quality.
Support project teams and project management by communicating with senior data managers, adapting to changing timelines, and contributing to training and documentation.

Job description

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: Operations
Internal Grade: 9
Direct Reports: No
Status: Exempt
Location: Remote in Poland

This 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 activities
- Interpret case report forms and match them against datasets to identify problems and questions
- Identify missing information based upon understanding of client’s study protocols and data collected
- Begin to identify and understand original data without client-provided data documentation
- Begin to identify derived variables by examining data and verify or confirm variables
- May create drafts of basic requirement documents
Create datasets based upon study protocols, data analysis plans and requirements with guidance from more senior data managers
- Create 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 Monolix
- Create complex datasets that include studies with complex designs and complicated data relationships, under supervision of more senior data managers
- Create dummy datasets based upon provided requirements
- Create simulation datasets based upon guidance from more senior data managers
- Understand and apply rules provided for data file creation for different modeling solutions
Understand and apply concept of data disposition
- Reconcile records from original to analysis dataset
- Create data deletion datasets to track deleted records based upon identified edit rules
- Review data disposition section of final technical report
Provide programming support to meet project objectives
- Write efficient code to meet project needs and seek guidance from more senior data managers on when to use advanced coding
- Read in raw data files and SAS datasets
- Creates listing, summary, HTML, and graph output and consult with more senior data managers to utilize advance features
- Investigate and summarize data by generating frequency tables and descriptive statistics
- Create variables and reassign data values, subsets data, and combines multiple files
- Develop and use standardized programs to facilitate the automation of routine programming tasks
- Design, write, and debug macro routines and understand how programs with and without macro code are processed
- Begin 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 direction
Perform 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 regression
Demonstrated 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 solving
- Critically evaluate and validate AI generated outputs
- Apply sound judgment to ensure accuracy, reproducibility, and compliance with established data management and quality standards
Create and maintain project documentation in accordance with all standard operating procedures
- Test all output to ensure it meets needs of project teams, based upon provided requirements and changes to requirements
- Perform additional testing of dataset creation, based upon knowledge of dataset content and stratification criteria
- Document pertinent programs written as part of an external project
- Follow Quality Management System procedures for file storage and naming conventions
- Follow standards for variable name and value assignment as defined by senior data managers and documented standards
- Assist in testing and documentation of new and revised software applications
Participate in project teams while following direction from the Data Management lead and/or project leader
- Ensure an appropriate level of communication with internal team members
- Understand changes in project direction, whether communicated verbally, electronically, or in writing
- Communicate information to senior data managers and work with more senior data managers when there are questions or problems with data
- Provide advice and make recommendations about data to scientists
Perform project management activities for assigned task
- Identify changes to timelines to determine impact upon assignments and meet the new deadlines
- Change direction of programming activities to accommodate project changes to ensure minimal interruption
- Understand study characteristics: for example, long-term objectives, data, and specific information, such as what population is being used
- May act as data management lead on a project for which there are several data managers, under supervision from more senior data managers
Identify and explore opportunities for professional development and training
- Attend internal and external training opportunities
- Remain current with technical reading
- Review material in industry-related publications regarding new methodologies and best practices performed by other companies, as identified by more senior data managers
- Contribute to departmental roundtable
- Provide internal training and make internal presentations
- Assist in developing presentations for external conferences and meetings
Identify complex problems and provide recommendations based upon analysis of the situation for assigned projects
Make decisions that impact tasks of an assigned project
Track time through project management system
Organize tasks and utilizes in-house management tools to ensure most efficient use of time
Comply with all policies and standard operating procedures as specified in the Quality Management System
Other duties as assigned

Qualifications:

2+ years of experience using R for data manipulation, analysis, and reporting in a scientific or analytical environment
Foundational familiarity with AI-assisted analytical or coding tools, with the ability to apply them thoughtfully and validate results in regulated or scientific contexts
Read and interpret manuals and technical documents and to communicate this interpretation effectively
Able to work with base R, tidyverse, or data.table, ggplot2
Extremely detail-oriented
Highly self-motivated and willing to take on challenges
Able to handle multiple tasks simultaneously
Able to work within tight deadlines
Possess effective critical-thinking, problem-solving, and organizational skills
Effective verbal and written communication skills
Effective presentation skills
Possess effective relationship-building skills with the ability to work closely with project leaders and team members
Work well independently with the demonstrated ability to work as a member of a team
Occasional travel for meetings and trainings

Education: