Data Scientist 

About the company and Role

Apton Biosystems is a biotechnology instrumentation platform company pioneering super-resolution DNA sequencing and single-molecule detection. We are looking for a highly motivated, skilled and creative Data Scientist to join our fast-paced and collaborative team. The successful candidate will be able to build and grow the Apton data analysis pipeline using state-of-the-art statistical analyses and a quantitative, first-principles mindset. She/he will work closely with a multidisciplinary group of scientists to play a key role in a continuous feedback loop of improving experimental data quality. The ideal candidate combines a strong passion for quantitative detail with the ability to communicate complex analyses with clarity to a multidisciplinary audience.

Key Responsibilities:

  • Accountable for the development of data analytics tools, predictive models, emergent insight capabilities & metrics
  • Take new analysis ideas from concept to integration into an automated analysis pipeline
  • Use statistical/scientific computer languages to draw actionable insights from large data sets
  • Perform data analysis on weekly next generation sequencing experiments
  • Perform analysis of customer data employing rigorous quality control standards
  • Generate data-driven hypotheses about biological processes
  • Reporting your hypotheses and findings to the team with clarity
  • Being a team player in a fast-paced startup environment


  • Masters or PhD in mathematics, (bio)informatics, computer science, or related field.
  • 2+ years of experience in data science in biology/physics or bioinformatics, preferably in sequencing applications
  • Expertise in NGS data analysis and algorithm development
  • Python programming experience (numpy/scipy/pandas/jupyter/matplotlib/…), comfortable in the Unix cli environment
  • Extensive experience with data analysis, visualization and interpretation
  • Experience with large dataset manipulation 
  • Strong interpersonal and communication skills


  • Familiarity with a wide range of bioinformatics packages and tools
  • Bayesian statistics, modeling & analysis approaches 
  • Database experience (SQL)
  • Experience with optimizing the performance of a biological system
  • Familiarity with machine learning packages (e.g. sk-learn, tensorflow)
  • Database experience/ working in a cloud-based environment 
  • Familiarity with packaging up data and version control