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Biostatistics Sr. Manager

Key Facts

Remote From: 
Category:  M&A Manager
Full time
Senior (5-10 years)
English

Other Skills

  • β€’
    Analytical Thinking
  • β€’
    Problem Solving
  • β€’
    Communication
  • β€’
    Collaboration

Roles & Responsibilities

  • Master's degree in Statistics, Biostatistics, Computer Science, Mathematics, Data Science, or a related quantitative field
  • 6+ years of relevant industry experience with a Master's degree, 4+ years with a PhD, or 10+ years with a Bachelor's degree
  • Strong programming skills in R and/or Python

Requirements:

  • Develop, maintain, and enhance analytical tools, applications, dashboards, and reporting solutions using R, R Shiny, and/or Python
  • Design and implement data analysis workflows, automated reporting pipelines, and AI-enabled solutions to support clinical analytics and decision-making
  • Build interactive visualizations and dashboards for data exploration, monitoring, and communication of insights

Job description

  • Client: global biotech company
  • Job: Biostatistics Sr. Manager
  • Location: 100% remote from anywhere in the US
  • Job Description:

We are seeking a highly motivated Biostatistics Sr. Manager to support clinical data analytics initiatives.

The successful candidate will collaborate with cross-functional teams to develop analytical tools, automate workflows, assess data quality, create interactive visualizations, and generate actionable insights from complex datasets using statistical, machine learning, and AI-driven approaches.

Responsibilities
  • Develop, maintain, and enhance analytical tools, applications, dashboards, and reporting solutions using R, R Shiny, and/or Python.
  • Design and implement data analysis workflows, automated reporting pipelines, and AI-enabled solutions to support clinical analytics and decision-making.
  • Build interactive visualizations and dashboards for data exploration, monitoring, and communication of insights.
  • Perform data quality assessments, validation, monitoring, and reconciliation activities to ensure data integrity and reliability.
  • Apply statistical methods, machine learning, and AI techniques to analyze complex datasets and address scientific and business challenges.
  • Collaborate with statisticians, data scientists, statistical programmers, software developers, and business stakeholders to deliver innovative analytical solutions.
  • Identify and implement process improvements, automation opportunities, and emerging technologies to enhance efficiency, scalability, and reproducibility.
  • Ensure compliance with applicable regulatory requirements, industry standards, and internal quality processes.
  • Document analytical methods, tools, workflows, and best practices according to organizational standards.
  • Stay current with emerging analytical methodologies, AI technologies, and industry best practices.

Required Qualifications

Education
  • Master's degree in Statistics, Biostatistics, Computer Science, Mathematics, Data Science, or a related quantitative field.
Experience and Skills
  • 6+ years of relevant industry experience with a Master's degree, 4+ years with a PhD, or 10+ years with a Bachelor's degree.
  • Proven experience applying statistical methods to clinical development, clinical research, healthcare, or related data.
  • Strong programming skills in R and/or Python, including experience developing analytical tools and applications.
  • Experience with R Shiny and/or other interactive reporting and visualization platforms.
  • Knowledge of statistical modeling, exploratory data analysis, and data quality methodologies.
  • Experience designing automated data analysis workflows and reporting solutions.
  • Experience applying machine learning and AI techniques to real-world analytical problems.
  • Proficiency in data manipulation, data wrangling, and workflow automation.
  • Familiarity with version control systems (e.g., Git) and software development best practices.
  • Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications
PhD in Statistics, Biostatistics, Computer Science, Mathematics, or a related quantitative field.
Experience in the pharmaceutical, biotechnology, healthcare, or clinical research industry.
Knowledge of clinical trial data standards and regulatory requirements, including CDISC SDTM and ADaM.
Experience building scalable analytics platforms, AI-enabled tools, automated reporting systems, or decision-support solutions.
Understanding of drug development processes and the clinical development lifecycle.Max Rate Not to
 

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