Hybrid Data Science Engineer

Posted 3 weeks ago

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About the role

  • Build and maintain scalable ETL pipelines for experimental, biological, and pharmacological data
  • Integrate data from multiple sources such as GeneData, LabVantage, CROs, and cloud platforms into unified analytical environments
  • Automate recurring workflows to ensure data quality, accessibility, and reproducibility
  • Collaborate with data scientists to implement and operationalize AI and machine learning models into production-ready pipelines on cloud and HPC environments
  • Monitor and maintain deployed models to ensure performance, scalability, and traceability
  • Develop scripts, APIs, and workflows to connect laboratory systems such as GeneData Biologics and LabVantage with central analytics environments
  • Act as the technical link between Discovery, IT, and Data Science teams
  • Translate scientific and technical needs into robust, scalable solutions
  • Provide responsive technical support to scientists to ensure data accessibility and workflow reliability.

Requirements

  • MSc in Computer Science, Data Science, Computational Biology, or a related field
  • Three to five years of relevant experience in data engineering or scientific data environments
  • Proficiency in Python and version control systems such as Git
  • Experience with AWS services including S3, Lambda, ECS, Glue, and Step Functions
  • Strong understanding of data integration, workflow automation, and pipeline design
  • Excellent communication skills with the ability to explain technical solutions clearly to scientific and technical colleagues
  • Proactive problem solver who can adapt quickly to changing priorities.

Benefits

  • Flexible working arrangements
  • Health and wellness programs

Job title

Data Science Engineer

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

No Education Requirement

Location requirements

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