Contextual Main Account Career

Data Scientist – Contextual Genomics

Job Description

Are you a data scientist with machine learning / artificial intelligence skillsets who strives to tackle the contemporary challenges in genomics-based cancer care?  Contextual Genomics is recruiting into its data science team with a focus on the analysis of large-scale cancer genomics datasets involving 1000s of patients, diagnostic images from matched tumour samples and longitudinal samples for predicting tumour progression. We are advancing cancer care for patients around the globe with a focus on delivering end to end solutions for the highest quality products. We are seeking PhD-level data scientists to accelerate data-driven research, accelerating advances in liquid biopsy, large scale patient population analyses, time-series monitoring of tumour progression and histology image analysis. Join us and complement our team of bioinformaticians, molecular biologists and pathologists contributing industry-leading platforms for global deployment of personalised medicine for cancer patients.

Main activities

  • Accelerate data-driven discovery from CG’s data assets to improve product development
  • Collaborate with data engineers to design, develop, and implement software and database solutions optimized for discovery-based R&D efforts
  • Work with research collaborators at leading academic institutions
  • Liaise with and collaborate with industry partners in pharma, biotech, health data, and big tech

We are seeking individuals who are

  • Science-focused with a track record of applying and/or developing analytical techniques for large scale datasets 
  • Attracted to quantitatively driven solutions and conclusions
  • Interested in methodology for the analysis of genomics and imaging 
  • A strong communicator and collaborator with a team-oriented mindset required to effectively collaborate with clinicians, biologists and engineers
  • Able to work effectively in a dynamic environment and adapt to occasional shifts in priorities


  • PhD in computer science, statistics, data science, bioinformatics, engineering or equivalent
  • Expert understanding of contemporary computational techniques such as deep learning & convolutional neural networks, variational autoencoders, Bayesian approaches, probabilistic graphical models, computational statistics, elementary statistics
  • Experience in at least one of image analysis, genomic analysis, clinical and health data analysis, natural language processing, multisensor data fusion
  • (Desired) experience in cloud computing environments
  • Specific skill sets: ScikitLearn, TensorFlow, PyTorch or similar