R&D Scientist – Scientific Data Analytics (d/f/m) Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology? At Genedata, one of Danaher’s operating companies, our work saves lives, and we’re all united by a shared commitment to innovate for tangible impact. You’ll thrive in a culture of belonging where your unique viewpoint matters. By harnessing Danaher’s system of continuous improvement, you help turn ideas into impact, innovating at the speed of life.
The biopharmaceutical industry is undergoing a transformation that requires advanced digitalization to adopt data‑ and AI‑driven approaches and develop innovative therapies quicker. Genedata’s market‑leading enterprise software fuels this transformation by enabling leading biopharma, biotech, and contract research as well as contract development and manufacturing organizations worldwide to automate processes and leverage data analytics and AI, so they can deliver breakthrough therapies to patients faster. Join us and help scientists around the world accelerate the pace of biopharma R&D.
Responsibilities
Conceptualize, design, prototype, and implement scientific data analysis workflows for Genedata Screener.
Translate advanced scientific methods into enterprise‑grade software components and licensable modules.
Collaborate in an agile/SCRUM environment with software engineers to deliver robust, production‑ready solutions.
Engage with pharmaceutical scientists to translate their requirements into automated data analysis workflows.
Analyze experimental life science data, perform feasibility studies, and ensure mathematical and statistical correctness of implemented methods.
Essential Requirements
PhD in physics, biophysics, applied mathematics, data science, bioinformatics, or a related quantitative field.
Multiple years of experience in scientific programming and workflow development.
Demonstrated experience with life science data analysis (e.g., high‑throughput screening, dose‑response analysis, biophysical assays).
Proficiency in Python and scientific computing libraries such as NumPy, SciPy, and pandas.
Experience delivering software solutions used by end users in a professional or enterprise setting.
Preferred Experience
Java programming.
Working in agile/SCRUM development environments.
Industry background in pharmaceutical, biotech, or contract research organizations.
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The biopharmaceutical industry is undergoing a transformation that requires advanced digitalization to adopt data‑ and AI‑driven approaches and develop innovative therapies quicker. Genedata’s market‑leading enterprise software fuels this transformation by enabling leading biopharma, biotech, and contract research as well as contract development and manufacturing organizations worldwide to automate processes and leverage data analytics and AI, so they can deliver breakthrough therapies to patients faster. Join us and help scientists around the world accelerate the pace of biopharma R&D.
Responsibilities
Conceptualize, design, prototype, and implement scientific data analysis workflows for Genedata Screener.
Translate advanced scientific methods into enterprise‑grade software components and licensable modules.
Collaborate in an agile/SCRUM environment with software engineers to deliver robust, production‑ready solutions.
Engage with pharmaceutical scientists to translate their requirements into automated data analysis workflows.
Analyze experimental life science data, perform feasibility studies, and ensure mathematical and statistical correctness of implemented methods.
Essential Requirements
PhD in physics, biophysics, applied mathematics, data science, bioinformatics, or a related quantitative field.
Multiple years of experience in scientific programming and workflow development.
Demonstrated experience with life science data analysis (e.g., high‑throughput screening, dose‑response analysis, biophysical assays).
Proficiency in Python and scientific computing libraries such as NumPy, SciPy, and pandas.
Experience delivering software solutions used by end users in a professional or enterprise setting.
Preferred Experience
Java programming.
Working in agile/SCRUM development environments.
Industry background in pharmaceutical, biotech, or contract research organizations.
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