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Data Science Engineer

Job in Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listing for: A2 Ai
Full Time position
Listed on 2026-07-13
Job specializations:
  • IT/Tech
    Data Engineering, AI Engineer (Applied/Software), Data Analyst, Data Scientist
Salary/Wage Range or Industry Benchmark: 110000 - 140000 USD Yearly USD 110000.00 140000.00 YEAR
Job Description & How to Apply Below
  • Develop and maintain analytical solutions, data products, and computational workflows that support scientific and business decision-making
  • Design and implement scalable data pipelines, analytical frameworks, and supporting infrastructure for biometrics, clinical pharmacology and pharmacometric analyses
  • Collaborate with scientists and technical teams to translate complex analytical requirements into robust, reusable solutions
  • Develop data visualization, reporting, and exploratory analysis tools to support internal and client-facing initiatives
  • Support the deployment, maintenance, and optimization of analytical solutions within A2-Ai Cloud and related computing environments
  • Develop reusable analytical frameworks, internal libraries, and software components that improve efficiency and reproducibility
  • Participate in testing, validation, troubleshooting, and documentation of analytical systems and workflows
  • Support the integration of AI, machine learning, and advanced analytics capabilities into scientific and operational solutions
  • Identify opportunities to improve analytical processes, data accessibility, and decision-support capabilities across the organization
Requirements
  • Bachelor's degree in data science, statistics, computer science, bioinformatics, engineering, or a related field, or equivalent experience developing analytical solutions and data-driven systems
  • Strong experience with R programming and data analysis packages such as ggplot2, dplyr, tidyr, and related analytical tools
  • Experience with Python, SQL, cloud-based workflows, or modern data engineering practices is preferred
  • Familiarity with pharmaceutical, biotech, clinical, or scientific data environments is preferred
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